R-universe search: derivatives

pharmaverse

admiral:ADaM in R Asset Library

A toolbox for programming Clinical Data Interchange Standards Consortium (CDISC) compliant Analysis Data Model (ADaM) datasets in R. ADaM datasets are a mandatory part of any New Drug or Biologics License Application submitted to the United States Food and Drug Administration (FDA). Analysis derivations are implemented in accordance with the "Analysis Data Model Implementation Guide" (CDISC Analysis Data Model Team, 2021, <https://www.cdisc.org/standards/foundational/adam>).

Maintained by Ben Straub. Last updated 5 days ago.

cdisc clinical-trials open-source

138.4 match 236 stars 13.89 score 486 scripts 4 dependents

sgsokol

Deriv:Symbolic Differentiation

R-based solution for symbolic differentiation. It admits user-defined function as well as function substitution in arguments of functions to be differentiated. Some symbolic simplification is part of the work.

Maintained by Serguei Sokol. Last updated 6 months ago.

58.3 match 39 stars 12.05 score 334 scripts 1.0k dependents

pharmaverse

admiralonco:Oncology Extension Package for ADaM in 'R' Asset Library

Programming oncology specific Clinical Data Interchange Standards Consortium (CDISC) compliant Analysis Data Model (ADaM) datasets in 'R'. ADaM datasets are a mandatory part of any New Drug or Biologics License Application submitted to the United States Food and Drug Administration (FDA). Analysis derivations are implemented in accordance with the "Analysis Data Model Implementation Guide" (CDISC Analysis Data Model Team (2021), <https://www.cdisc.org/standards/foundational/adam>). The package is an extension package of the 'admiral' package.

Maintained by Stefan Bundfuss. Last updated 2 months ago.

78.1 match 32 stars 8.66 score 30 scripts

nlmixr2

rxode2:Facilities for Simulating from ODE-Based Models

Facilities for running simulations from ordinary differential equation ('ODE') models, such as pharmacometrics and other compartmental models. A compilation manager translates the ODE model into C, compiles it, and dynamically loads the object code into R for improved computational efficiency. An event table object facilitates the specification of complex dosing regimens (optional) and sampling schedules. NB: The use of this package requires both C and Fortran compilers, for details on their use with R please see Section 6.3, Appendix A, and Appendix D in the "R Administration and Installation" manual. Also the code is mostly released under GPL. The 'VODE' and 'LSODA' are in the public domain. The information is available in the inst/COPYRIGHTS.

Maintained by Matthew L. Fidler. Last updated 30 days ago.

fortran openblas cpp openmp

47.2 match 40 stars 11.24 score 220 scripts 13 dependents

teos-10

gsw:Gibbs Sea Water Functions

Provides an interface to the Gibbs 'SeaWater' ('TEOS-10') C library, version 3.06-16-0 (commit '657216dd4f5ea079b5f0e021a4163e2d26893371', dated 2022-10-11, available at <https://github.com/TEOS-10/GSW-C>, which stems from 'Matlab' and other code written by members of Working Group 127 of 'SCOR'/'IAPSO' (Scientific Committee on Oceanic Research / International Association for the Physical Sciences of the Oceans).

Maintained by Dan Kelley. Last updated 9 days ago.

gibbs oceanography seawater teos-10

53.0 match 8 stars 8.53 score 286 scripts 19 dependents

pharmaverse

admiralvaccine:Vaccine Extension Package for ADaM in 'R' Asset Library

Programming vaccine specific Clinical Data Interchange Standards Consortium (CDISC) compliant Analysis Data Model (ADaM) datasets in 'R'. Flat model is followed as per Center for Biologics Evaluation and Research (CBER) guidelines for creating vaccine specific domains. ADaM datasets are a mandatory part of any New Drug or Biologics License Application submitted to the United States Food and Drug Administration (FDA). Analysis derivations are implemented in accordance with the "Analysis Data Model Implementation Guide" (CDISC Analysis Data Model Team (2021), <https://www.cdisc.org/standards/foundational/adam/adamig-v1-3-release-package>). The package is an extension package of the 'admiral' package.

Maintained by Sukalpo Saha. Last updated 2 months ago.

cdisc

38.8 match 6 stars 7.44 score 23 scripts

nashjc

nlsr:Functions for Nonlinear Least Squares Solutions - Updated 2022

Provides tools for working with nonlinear least squares problems. For the estimation of models reliable and robust tools than nls(), where the the Gauss-Newton method frequently stops with 'singular gradient' messages. This is accomplished by using, where possible, analytic derivatives to compute the matrix of derivatives and a stabilization of the solution of the estimation equations. Tools for approximate or externally supplied derivative matrices are included. Bounds and masks on parameters are handled properly.

Maintained by John C Nash. Last updated 27 days ago.

34.1 match 7.02 score 94 scripts 5 dependents

eguidotti

calculus:High Dimensional Numerical and Symbolic Calculus

Efficient C++ optimized functions for numerical and symbolic calculus as described in Guidotti (2022) <doi:10.18637/jss.v104.i05>. It includes basic arithmetic, tensor calculus, Einstein summing convention, fast computation of the Levi-Civita symbol and generalized Kronecker delta, Taylor series expansion, multivariate Hermite polynomials, high-order derivatives, ordinary differential equations, differential operators (Gradient, Jacobian, Hessian, Divergence, Curl, Laplacian) and numerical integration in arbitrary orthogonal coordinate systems: cartesian, polar, spherical, cylindrical, parabolic or user defined by custom scale factors.

Maintained by Emanuele Guidotti. Last updated 2 years ago.

calculus coordinate-systems curl divergence einstein finite-difference gradient hermite hessian jacobian laplacian numerical-derivation numerical-derivatives numerical-differentiation symbolic-computation symbolic-differentiation taylor cpp

23.5 match 47 stars 8.92 score 66 scripts 7 dependents

gavinsimpson

gratia:Graceful 'ggplot'-Based Graphics and Other Functions for GAMs Fitted Using 'mgcv'

Graceful 'ggplot'-based graphics and utility functions for working with generalized additive models (GAMs) fitted using the 'mgcv' package. Provides a reimplementation of the plot() method for GAMs that 'mgcv' provides, as well as 'tidyverse' compatible representations of estimated smooths.

Maintained by Gavin L. Simpson. Last updated 14 hours ago.

distributional-regression gam gamm generalized-additive-mixed-models generalized-additive-models ggplot2 glm lm mgcv penalized-spline random-effects smoothing splines

13.8 match 217 stars 12.99 score 1.6k scripts 2 dependents

fifis

pnd:Parallel Numerical Derivatives, Gradients, Jacobians, and Hessians of Arbitrary Accuracy Order

Numerical derivatives through finite-difference approximations can be calculated using the 'pnd' package with parallel capabilities and optimal step-size selection to improve accuracy. These functions facilitate efficient computation of derivatives, gradients, Jacobians, and Hessians, allowing for more evaluations to reduce the mathematical and machine errors. Designed for compatibility with the 'numDeriv' package, which has not received updates in several years, it introduces advanced features such as computing derivatives of arbitrary order, improving the accuracy of Hessian approximations by avoiding repeated differencing, and parallelising slow functions on Windows, Mac, and Linux.

Maintained by Andreï Victorovitch Kostyrka. Last updated 6 days ago.

33.9 match 1 stars 5.22 score 5 scripts

collinerickson

GauPro:Gaussian Process Fitting

Fits a Gaussian process model to data. Gaussian processes are commonly used in computer experiments to fit an interpolating model. The model is stored as an 'R6' object and can be easily updated with new data. There are options to run in parallel, and 'Rcpp' has been used to speed up calculations. For more info about Gaussian process software, see Erickson et al. (2018) <doi:10.1016/j.ejor.2017.10.002>.

Maintained by Collin Erickson. Last updated 11 hours ago.

openblas cpp openmp

20.7 match 16 stars 8.44 score 104 scripts 1 dependents

crunch-io

crunch:Crunch.io Data Tools

The Crunch.io service <https://crunch.io/> provides a cloud-based data store and analytic engine, as well as an intuitive web interface. Using this package, analysts can interact with and manipulate Crunch datasets from within R. Importantly, this allows technical researchers to collaborate naturally with team members, managers, and clients who prefer a point-and-click interface.

Maintained by Greg Freedman Ellis. Last updated 11 days ago.

16.4 match 9 stars 10.53 score 200 scripts 2 dependents

jonesor

Rage:Life History Metrics from Matrix Population Models

Functions for calculating life history metrics using matrix population models ('MPMs'). Described in Jones et al. (2021) <doi:10.1101/2021.04.26.441330>.

Maintained by Owen Jones. Last updated 3 months ago.

19.3 match 11 stars 8.17 score 62 scripts 1 dependents

wenjie2wang

splines2:Regression Spline Functions and Classes

Constructs basis functions of B-splines, M-splines, I-splines, convex splines (C-splines), periodic splines, natural cubic splines, generalized Bernstein polynomials, their derivatives, and integrals (except C-splines) by closed-form recursive formulas. It also contains a C++ head-only library integrated with Rcpp. See Wang and Yan (2021) <doi:10.6339/21-JDS1020> for details.

Maintained by Wenjie Wang. Last updated 12 days ago.

derivative integral rcpp splines openblas cpp

13.6 match 43 stars 11.46 score 394 scripts 34 dependents

wasquith

copBasic:General Bivariate Copula Theory and Many Utility Functions

Extensive functions for bivariate copula (bicopula) computations and related operations for bicopula theory. The lower, upper, product, and select other bicopula are implemented along with operations including the diagonal, survival copula, dual of a copula, co-copula, and numerical bicopula density. Level sets, horizontal and vertical sections are supported. Numerical derivatives and inverses of a bicopula are provided through which simulation is implemented. Bicopula composition, convex combination, asymmetry extension, and products also are provided. Support extends to the Kendall Function as well as the Lmoments thereof. Kendall Tau, Spearman Rho and Footrule, Gini Gamma, Blomqvist Beta, Hoeffding Phi, Schweizer- Wolff Sigma, tail dependency, tail order, skewness, and bivariate Lmoments are implemented, and positive/negative quadrant dependency, left (right) increasing (decreasing) are available. Other features include Kullback-Leibler Divergence, Vuong Procedure, spectral measure, and Lcomoments for inference, maximum likelihood, and AIC, BIC, and RMSE for goodness-of-fit.

Maintained by William Asquith. Last updated 1 months ago.

27.7 match 5.34 score 139 scripts 5 dependents

mvogel78

childsds:Data and Methods Around Reference Values in Pediatrics

Calculation of standard deviation scores and percentiles adduced from different standards (WHO, UK, Germany, Italy, China, etc). Also, references for laboratory values in children and adults are available, e.g., serum lipids, iron-related blood parameters, IGF, liver enzymes. See package documentation for full list.

Maintained by Mandy Vogel. Last updated 2 months ago.

50.6 match 2.83 score 51 scripts

pharmaverse

admiralophtha:ADaM in R Asset Library - Ophthalmology

Aids the programming of Clinical Data Standards Interchange Consortium (CDISC) compliant Ophthalmology Analysis Data Model (ADaM) datasets in R. ADaM datasets are a mandatory part of any New Drug or Biologics License Application submitted to the United States Food and Drug Administration (FDA). Analysis derivations are implemented in accordance with the "Analysis Data Model Implementation Guide" (CDISC Analysis Data Model Team, 2021, <https://www.cdisc.org/standards/foundational/adam/adamig-v1-3-release-package>).

Maintained by Edoardo Mancini. Last updated 2 months ago.

17.7 match 15 stars 7.94 score 10 scripts

l-ramirez-lopez

prospectr:Miscellaneous Functions for Processing and Sample Selection of Spectroscopic Data

Functions to preprocess spectroscopic data and conduct (representative) sample selection/calibration sampling.

Maintained by Leonardo Ramirez-Lopez. Last updated 11 days ago.

chemometrics derivatives infrared near-infrared nir pedometrics preprocessing resample sampling signal soil-spectroscopy spectroscopy openblas cpp openmp

14.0 match 42 stars 10.00 score 326 scripts 4 dependents

tyee001

VGAM:Vector Generalized Linear and Additive Models

An implementation of about 6 major classes of statistical regression models. The central algorithm is Fisher scoring and iterative reweighted least squares. At the heart of this package are the vector generalized linear and additive model (VGLM/VGAM) classes. VGLMs can be loosely thought of as multivariate GLMs. VGAMs are data-driven VGLMs that use smoothing. The book "Vector Generalized Linear and Additive Models: With an Implementation in R" (Yee, 2015) <DOI:10.1007/978-1-4939-2818-7> gives details of the statistical framework and the package. Currently only fixed-effects models are implemented. Many (100+) models and distributions are estimated by maximum likelihood estimation (MLE) or penalized MLE. The other classes are RR-VGLMs (reduced-rank VGLMs), quadratic RR-VGLMs, doubly constrained RR-VGLMs, quadratic RR-VGLMs, reduced-rank VGAMs, RCIMs (row-column interaction models)---these classes perform constrained and unconstrained quadratic ordination (CQO/UQO) models in ecology, as well as constrained additive ordination (CAO). Hauck-Donner effect detection is implemented. Note that these functions are subject to change; see the NEWS and ChangeLog files for latest changes.

Maintained by Thomas Yee. Last updated 1 months ago.

fortran

11.9 match 10 stars 10.67 score 3.6k scripts 169 dependents

rtdists

fddm:Fast Implementation of the Diffusion Decision Model

Provides the probability density function (PDF), cumulative distribution function (CDF), the first-order and second-order partial derivatives of the PDF, and a fitting function for the diffusion decision model (DDM; e.g., Ratcliff & McKoon, 2008, <doi:10.1162/neco.2008.12-06-420>) with across-trial variability in the drift rate. Because the PDF, its partial derivatives, and the CDF of the DDM both contain an infinite sum, they need to be approximated. 'fddm' implements all published approximations (Navarro & Fuss, 2009, <doi:10.1016/j.jmp.2009.02.003>; Gondan, Blurton, & Kesselmeier, 2014, <doi:10.1016/j.jmp.2014.05.002>; Blurton, Kesselmeier, & Gondan, 2017, <doi:10.1016/j.jmp.2016.11.003>; Hartmann & Klauer, 2021, <doi:10.1016/j.jmp.2021.102550>) plus new approximations. All approximations are implemented purely in 'C++' providing faster speed than existing packages.

Maintained by Henrik Singmann. Last updated 8 months ago.

cpp

20.4 match 14 stars 6.24 score 2 scripts

shivaway

IAPWS95:Thermophysical Properties of Water and Steam

Functions for Water and Steam Properties based on the International Association for the Properties of Water (IAPWS) Formulation 1995 for the Thermodynamic Properties of Ordinary Water Substance for General and Scientific Use and on the releases for viscosity, conductivity, surface tension and melting pressure.

Maintained by Shawn Way. Last updated 2 years ago.

fortran glibc

26.4 match 4.76 score 116 scripts

hwborchers

pracma:Practical Numerical Math Functions

Provides a large number of functions from numerical analysis and linear algebra, numerical optimization, differential equations, time series, plus some well-known special mathematical functions. Uses 'MATLAB' function names where appropriate to simplify porting.

Maintained by Hans W. Borchers. Last updated 1 years ago.

10.1 match 29 stars 12.34 score 6.6k scripts 931 dependents

nanxstats

protr:Generating Various Numerical Representation Schemes for Protein Sequences

Comprehensive toolkit for generating various numerical features of protein sequences described in Xiao et al. (2015) <DOI:10.1093/bioinformatics/btv042>. For full functionality, the software 'ncbi-blast+' is needed, see <https://blast.ncbi.nlm.nih.gov/doc/blast-help/downloadblastdata.html> for more information.

Maintained by Nan Xiao. Last updated 6 months ago.

bioinformatics feature-engineering feature-extraction machine-learning peptides protein-sequences sequence-analysis

11.9 match 52 stars 10.02 score 173 scripts 3 dependents

nlmixr2

rxode2ll:Log-Likelihood Functions for 'rxode2'

Provides the log-likelihoods with gradients from 'stan' (Carpenter et al (2015), <doi:10.48550/arXiv.1509.07164>) needed for generalized log-likelihood estimation in 'nlmixr2' (Fidler et al (2019) <doi:10.1002/psp4.12445>). This is split of to reduce computational burden of recompiling 'rxode2' (Wang, Hallow and James (2016) <doi:10.1002/psp4.12052>) which runs the 'nlmixr2' models during estimation.

Maintained by Matthew L. Fidler. Last updated 3 months ago.

cpp

23.0 match 2 stars 5.14 score 1 scripts 14 dependents

r-forge

numDeriv:Accurate Numerical Derivatives

Methods for calculating (usually) accurate numerical first and second order derivatives. Accurate calculations are done using 'Richardson''s' extrapolation or, when applicable, a complex step derivative is available. A simple difference method is also provided. Simple difference is (usually) less accurate but is much quicker than 'Richardson''s' extrapolation and provides a useful cross-check. Methods are provided for real scalar and vector valued functions.

Maintained by Paul Gilbert. Last updated 2 months ago.

8.1 match 1 stars 14.10 score 1.2k scripts 3.1k dependents

bioc

Rcpi:Molecular Informatics Toolkit for Compound-Protein Interaction in Drug Discovery

A molecular informatics toolkit with an integration of bioinformatics and chemoinformatics tools for drug discovery.

Maintained by Nan Xiao. Last updated 5 months ago.

software dataimport datarepresentation featureextraction cheminformatics biomedicalinformatics proteomics go systemsbiology bioconductor bioinformatics drug-discovery feature-extraction fingerprint molecular-descriptors protein-sequences

14.7 match 37 stars 7.81 score 29 scripts

raphaelhartmann

WienR:Derivatives of the First-Passage Time Density and Cumulative Distribution Function, and Random Sampling from the (Truncated) First-Passage Time Distribution

First, we provide functions to calculate the partial derivative of the first-passage time diffusion probability density function (PDF) and cumulative distribution function (CDF) with respect to the first-passage time t (only for PDF), the upper barrier a, the drift rate v, the relative starting point w, the non-decision time t0, the inter-trial variability of the drift rate sv, the inter-trial variability of the rel. starting point sw, and the inter-trial variability of the non-decision time st0. In addition the PDF and CDF themselves are also provided. Most calculations are done on the logarithmic scale to make it more stable. Since the PDF, CDF, and their derivatives are represented as infinite series, we give the user the option to control the approximation errors with the argument 'precision'. For the numerical integration we used the C library cubature by Johnson, S. G. (2005-2013) <https://github.com/stevengj/cubature>. Numerical integration is required whenever sv, sw, and/or st0 is not zero. Note that numerical integration reduces speed of the computation and the precision cannot be guaranteed anymore. Therefore, whenever numerical integration is used an estimate of the approximation error is provided in the output list. Note: The large number of contributors (ctb) is due to copying a lot of C/C++ code chunks from the GNU Scientific Library (GSL). Second, we provide methods to sample from the first-passage time distribution with or without user-defined truncation from above. The first method is a new adaptive rejection sampler building on the works of Gilks and Wild (1992; <doi:10.2307/2347565>) and Hartmann and Klauer (in press). The second method is a rejection sampler provided by Drugowitsch (2016; <doi:10.1038/srep20490>). The third method is an inverse transformation sampler. The fourth method is a "pseudo" adaptive rejection sampler that builds on the first method. For more details see the corresponding help files.

Maintained by Raphael Hartmann. Last updated 1 years ago.

cpp

30.7 match 2 stars 3.48 score 3 scripts 1 dependents

walkerke

tidycensus:Load US Census Boundary and Attribute Data as 'tidyverse' and 'sf'-Ready Data Frames

An integrated R interface to several United States Census Bureau APIs (<https://www.census.gov/data/developers/data-sets.html>) and the US Census Bureau's geographic boundary files. Allows R users to return Census and ACS data as tidyverse-ready data frames, and optionally returns a list-column with feature geometry for mapping and spatial analysis.

Maintained by Kyle Walker. Last updated 2 months ago.

7.2 match 647 stars 14.27 score 7.5k scripts 10 dependents

imanuelcostigan

dataonderivatives:Easily Source Publicly Available Data on Derivatives

Post Global Financial Crisis derivatives reforms have lifted the veil off over-the-counter (OTC) derivative markets. Swap Execution Facilities (SEFs) and Swap Data Repositories (SDRs) now publish data on swaps that are traded on or reported to those facilities (respectively). This package provides you the ability to get this data from supported sources.

Maintained by Imanuel Costigan. Last updated 3 years ago.

derivative derivatives

23.7 match 37 stars 4.27 score 9 scripts

cran

mgcv:Mixed GAM Computation Vehicle with Automatic Smoothness Estimation

Generalized additive (mixed) models, some of their extensions and other generalized ridge regression with multiple smoothing parameter estimation by (Restricted) Marginal Likelihood, Generalized Cross Validation and similar, or using iterated nested Laplace approximation for fully Bayesian inference. See Wood (2017) <doi:10.1201/9781315370279> for an overview. Includes a gam() function, a wide variety of smoothers, 'JAGS' support and distributions beyond the exponential family.

Maintained by Simon Wood. Last updated 1 years ago.

openblas openmp

7.9 match 32 stars 12.71 score 17k scripts 7.8k dependents

iagogv3

kedd:Kernel Estimator and Bandwidth Selection for Density and Its Derivatives

Smoothing techniques and computing bandwidth selectors of the nth derivative of a probability density for one-dimensional data (described in Arsalane Chouaib Guidoum (2020) <arXiv:2012.06102> [stat.CO]).

Maintained by Iago Giné-Vázquez. Last updated 1 years ago.

19.1 match 5.23 score 57 scripts 1 dependents

tarnduong

ks:Kernel Smoothing

Kernel smoothers for univariate and multivariate data, with comprehensive visualisation and bandwidth selection capabilities, including for densities, density derivatives, cumulative distributions, clustering, classification, density ridges, significant modal regions, and two-sample hypothesis tests. Chacon & Duong (2018) <doi:10.1201/9780429485572>.

Maintained by Tarn Duong. Last updated 6 months ago.

9.6 match 6 stars 10.14 score 920 scripts 262 dependents

jamesramsay5

fda:Functional Data Analysis

These functions were developed to support functional data analysis as described in Ramsay, J. O. and Silverman, B. W. (2005) Functional Data Analysis. New York: Springer and in Ramsay, J. O., Hooker, Giles, and Graves, Spencer (2009). Functional Data Analysis with R and Matlab (Springer). The package includes data sets and script files working many examples including all but one of the 76 figures in this latter book. Matlab versions are available by ftp from <https://www.psych.mcgill.ca/misc/fda/downloads/FDAfuns/>.

Maintained by James Ramsay. Last updated 4 months ago.

7.8 match 3 stars 12.29 score 2.0k scripts 143 dependents

bioc

TCGAbiolinks:TCGAbiolinks: An R/Bioconductor package for integrative analysis with GDC data

The aim of TCGAbiolinks is : i) facilitate the GDC open-access data retrieval, ii) prepare the data using the appropriate pre-processing strategies, iii) provide the means to carry out different standard analyses and iv) to easily reproduce earlier research results. In more detail, the package provides multiple methods for analysis (e.g., differential expression analysis, identifying differentially methylated regions) and methods for visualization (e.g., survival plots, volcano plots, starburst plots) in order to easily develop complete analysis pipelines.

Maintained by Tiago Chedraoui Silva. Last updated 27 days ago.

dnamethylation differentialmethylation generegulation geneexpression methylationarray differentialexpression pathways network sequencing survival software bioc bioconductor gdc integrative-analysis tcga tcga-data tcgabiolinks

6.6 match 305 stars 14.45 score 1.6k scripts 6 dependents

keaven

gsDesign:Group Sequential Design

Derives group sequential clinical trial designs and describes their properties. Particular focus on time-to-event, binary, and continuous outcomes. Largely based on methods described in Jennison, Christopher and Turnbull, Bruce W., 2000, "Group Sequential Methods with Applications to Clinical Trials" ISBN: 0-8493-0316-8.

Maintained by Keaven Anderson. Last updated 12 days ago.

biostatistics boundaries clinical-trials design spending-functions

7.2 match 51 stars 13.05 score 338 scripts 5 dependents

pecanproject

PEcAn.DB:PEcAn Functions Used for Ecological Forecasts and Reanalysis

The Predictive Ecosystem Carbon Analyzer (PEcAn) is a scientific workflow management tool that is designed to simplify the management of model parameterization, execution, and analysis. The goal of PECAn is to streamline the interaction between data and models, and to improve the efficacy of scientific investigation.

Maintained by David LeBauer. Last updated 2 days ago.

bayesian cyberinfrastructure data-assimilation data-science ecosystem-model ecosystem-science forecasting meta-analysis national-science-foundation pecan plants

7.8 match 216 stars 11.88 score 127 scripts 27 dependents

murrayefford

secr:Spatially Explicit Capture-Recapture

Functions to estimate the density and size of a spatially distributed animal population sampled with an array of passive detectors, such as traps, or by searching polygons or transects. Models incorporating distance-dependent detection are fitted by maximizing the likelihood. Tools are included for data manipulation and model selection.

Maintained by Murray Efford. Last updated 3 hours ago.

cpp

9.1 match 3 stars 10.14 score 410 scripts 5 dependents

tpook92

MoBPS:Modular Breeding Program Simulator

Framework for the simulation framework for the simulation of complex breeding programs and compare their economic and genetic impact. The package is also used as the background simulator for our a web-based interface <http:www.mobps.de>. Associated publication: Pook et al. (2020) <doi:10.1534/g3.120.401193>.

Maintained by Torsten Pook. Last updated 3 years ago.

37.5 match 2.35 score 45 scripts

big-life-lab

recodeflow:Contains functions to interface with variable details sheets, including recoding variables and converting them to PMML

Recode and harmonize data using variable and details sheets.

Maintained by Yulric Sequeria. Last updated 6 days ago.

12.8 match 6 stars 6.75 score 7 scripts

openpharma

mmrm:Mixed Models for Repeated Measures

Mixed models for repeated measures (MMRM) are a popular choice for analyzing longitudinal continuous outcomes in randomized clinical trials and beyond; see Cnaan, Laird and Slasor (1997) <doi:10.1002/(SICI)1097-0258(19971030)16:20%3C2349::AID-SIM667%3E3.0.CO;2-E> for a tutorial and Mallinckrodt, Lane, Schnell, Peng and Mancuso (2008) <doi:10.1177/009286150804200402> for a review. This package implements MMRM based on the marginal linear model without random effects using Template Model Builder ('TMB') which enables fast and robust model fitting. Users can specify a variety of covariance matrices, weight observations, fit models with restricted or standard maximum likelihood inference, perform hypothesis testing with Satterthwaite or Kenward-Roger adjustment, and extract least square means estimates by using 'emmeans'.

Maintained by Daniel Sabanes Bove. Last updated 10 days ago.

cpp

6.9 match 138 stars 12.15 score 113 scripts 4 dependents

myominnoo

u5mr:Under-Five Child Mortality Estimation

Contains functions for calculating under-five child mortality estimates using the Trussell version of the Brass method (United Nations (1990) <https://www.un.org/en/development/desa/population/publications/pdf/mortality/stepguide_childmort.pdf> and United Nations (1983) <https://www.un.org/en/development/desa/population/publications/pdf/mortality/stepguide_childmort.pdf>) as well as applying the cohort-derived methods by Rajaratnam and colleagues (Rajaratnam JK, Tran LN, Lopez AD, Murray CJL (2010) "Measuring Under-Five Mortality: Validation of New Low-Cost Methods" <doi:10.1371/journal.pmed.1000253>).

Maintained by Myo Minn Oo. Last updated 4 years ago.

30.8 match 1 stars 2.70 score 5 scripts

projectmosaic

mosaicCalc:R-Language Based Calculus Operations for Teaching

Software to support the introductory *MOSAIC Calculus* textbook <https://www.mosaic-web.org/MOSAIC-Calculus/>), one of many data- and modeling-oriented educational resources developed by Project MOSAIC (<https://www.mosaic-web.org/>). Provides symbolic and numerical differentiation and integration, as well as support for applied linear algebra (for data science), and differential equations/dynamics. Includes grammar-of-graphics-based functions for drawing vector fields, trajectories, etc. The software is suitable for general use, but intended mainly for teaching calculus.

Maintained by Daniel Kaplan. Last updated 20 days ago.

9.5 match 13 stars 8.68 score 546 scripts

eliocamp

metR:Tools for Easier Analysis of Meteorological Fields

Many useful functions and extensions for dealing with meteorological data in the tidy data framework. Extends 'ggplot2' for better plotting of scalar and vector fields and provides commonly used analysis methods in the atmospheric sciences.

Maintained by Elio Campitelli. Last updated 21 days ago.

atmospheric-science ggplot2 visualization

6.8 match 144 stars 12.19 score 1000 scripts 22 dependents

mikeblazanin

gcplyr:Wrangle and Analyze Growth Curve Data

Easy wrangling and model-free analysis of microbial growth curve data, as commonly output by plate readers. Tools for reshaping common plate reader outputs into 'tidy' formats and merging them with design information, making data easy to work with using 'gcplyr' and other packages. Also streamlines common growth curve processing steps, like smoothing and calculating derivatives, and facilitates model-free characterization and analysis of growth data. See methods at <https://mikeblazanin.github.io/gcplyr/>.

Maintained by Mike Blazanin. Last updated 2 months ago.

dplyr ggplot2 tidyverse

10.4 match 30 stars 7.90 score 75 scripts

bioc

baySeq:Empirical Bayesian analysis of patterns of differential expression in count data

This package identifies differential expression in high-throughput 'count' data, such as that derived from next-generation sequencing machines, calculating estimated posterior likelihoods of differential expression (or more complex hypotheses) via empirical Bayesian methods.

Maintained by Samuel Granjeaud. Last updated 5 months ago.

sequencing differentialexpression multiplecomparison sage bayesian coverage

10.4 match 7.75 score 79 scripts 3 dependents

tnagler

VineCopula:Statistical Inference of Vine Copulas

Provides tools for the statistical analysis of regular vine copula models, see Aas et al. (2009) <doi:10.1016/j.insmatheco.2007.02.001> and Dissman et al. (2013) <doi:10.1016/j.csda.2012.08.010>. The package includes tools for parameter estimation, model selection, simulation, goodness-of-fit tests, and visualization. Tools for estimation, selection and exploratory data analysis of bivariate copula models are also provided.

Maintained by Thomas Nagler. Last updated 24 days ago.

copula estimation statistics vine

7.2 match 91 stars 10.99 score 362 scripts 23 dependents

functionaldata

fdapace:Functional Data Analysis and Empirical Dynamics

A versatile package that provides implementation of various methods of Functional Data Analysis (FDA) and Empirical Dynamics. The core of this package is Functional Principal Component Analysis (FPCA), a key technique for functional data analysis, for sparsely or densely sampled random trajectories and time courses, via the Principal Analysis by Conditional Estimation (PACE) algorithm. This core algorithm yields covariance and mean functions, eigenfunctions and principal component (scores), for both functional data and derivatives, for both dense (functional) and sparse (longitudinal) sampling designs. For sparse designs, it provides fitted continuous trajectories with confidence bands, even for subjects with very few longitudinal observations. PACE is a viable and flexible alternative to random effects modeling of longitudinal data. There is also a Matlab version (PACE) that contains some methods not available on fdapace and vice versa. Updates to fdapace were supported by grants from NIH Echo and NSF DMS-1712864 and DMS-2014626. Please cite our package if you use it (You may run the command citation("fdapace") to get the citation format and bibtex entry). References: Wang, J.L., Chiou, J., Müller, H.G. (2016) <doi:10.1146/annurev-statistics-041715-033624>; Chen, K., Zhang, X., Petersen, A., Müller, H.G. (2017) <doi:10.1007/s12561-015-9137-5>.

Maintained by Yidong Zhou. Last updated 9 months ago.

cpp

6.8 match 31 stars 11.46 score 474 scripts 25 dependents

bioc

ROSeq:Modeling expression ranks for noise-tolerant differential expression analysis of scRNA-Seq data

ROSeq - A rank based approach to modeling gene expression with filtered and normalized read count matrix. ROSeq takes filtered and normalized read matrix and cell-annotation/condition as input and determines the differentially expressed genes between the contrasting groups of single cells. One of the input parameters is the number of cores to be used.

Maintained by Krishan Gupta. Last updated 5 months ago.

geneexpression differentialexpression singlecell count-data gene-expression gene-expression-profiles normalization populations rank tmm tung tung-dataset tutorial vignette

17.9 match 2 stars 4.34 score 11 scripts

poissonconsulting

mcmcderive:Derive MCMC Parameters

Generates derived parameter(s) from Monte Carlo Markov Chain (MCMC) samples using R code. This allows Bayesian models to be fitted without the inclusion of derived parameters which add unnecessary clutter and slow model fitting. For more information on MCMC samples see Brooks et al. (2011) <isbn:978-1-4200-7941-8>.

Maintained by Joe Thorley. Last updated 1 months ago.

derived-parameters mcmc mcmcr

13.9 match 5.53 score 5 scripts 8 dependents

mcanouil

eggla:Early Growth Genetics Longitudinal Analysis

Tools for longitudinal analysis within the EGG (Early Growth Genetics) Consortium (<http://egg-consortium.org/>).

Maintained by Mickaël Canouil. Last updated 1 months ago.

genetics growth-curves infancy longitudinal-analysis mixed-effects-models spline-regression

18.3 match 3 stars 4.15 score 19 scripts

tidyverse

ggplot2:Create Elegant Data Visualisations Using the Grammar of Graphics

A system for 'declaratively' creating graphics, based on "The Grammar of Graphics". You provide the data, tell 'ggplot2' how to map variables to aesthetics, what graphical primitives to use, and it takes care of the details.

Maintained by Thomas Lin Pedersen. Last updated 9 days ago.

data-visualisation visualisation

3.0 match 6.6k stars 25.10 score 645k scripts 7.5k dependents

nimble-dev

nimble:MCMC, Particle Filtering, and Programmable Hierarchical Modeling

A system for writing hierarchical statistical models largely compatible with 'BUGS' and 'JAGS', writing nimbleFunctions to operate models and do basic R-style math, and compiling both models and nimbleFunctions via custom-generated C++. 'NIMBLE' includes default methods for MCMC, Laplace Approximation, Monte Carlo Expectation Maximization, and some other tools. The nimbleFunction system makes it easy to do things like implement new MCMC samplers from R, customize the assignment of samplers to different parts of a model from R, and compile the new samplers automatically via C++ alongside the samplers 'NIMBLE' provides. 'NIMBLE' extends the 'BUGS'/'JAGS' language by making it extensible: New distributions and functions can be added, including as calls to external compiled code. Although most people think of MCMC as the main goal of the 'BUGS'/'JAGS' language for writing models, one can use 'NIMBLE' for writing arbitrary other kinds of model-generic algorithms as well. A full User Manual is available at <https://r-nimble.org>.

Maintained by Christopher Paciorek. Last updated 5 days ago.

bayesian-inference bayesian-methods hierarchical-models mcmc probabilistic-programming openblas cpp

5.8 match 169 stars 12.97 score 2.6k scripts 19 dependents

welch-lab

cytosignal:What the Package Does (One Line, Title Case)

What the package does (one paragraph).

Maintained by Jialin Liu. Last updated 6 days ago.

openblas cpp

12.4 match 16 stars 5.95 score 6 scripts

dcourvoisier

doremi:Dynamics of Return to Equilibrium During Multiple Inputs

Provides models to fit the dynamics of a regulated system experiencing exogenous inputs. The underlying models use differential equations and linear mixed-effects regressions to estimate the coefficients of the equation. With them, the functions can provide an estimated signal. The package provides simulation and analysis functions and also print, summary, plot and predict methods, adapted to the function outputs, for easy implementation and presentation of results.

Maintained by Mongin Denis. Last updated 3 years ago.

15.9 match 4.48 score 25 scripts 1 dependents

julienvollering

MIAmaxent:A Modular, Integrated Approach to Maximum Entropy Distribution Modeling

Tools for training, selecting, and evaluating maximum entropy (and standard logistic regression) distribution models. This package provides tools for user-controlled transformation of explanatory variables, selection of variables by nested model comparison, and flexible model evaluation and projection. It follows principles based on the maximum- likelihood interpretation of maximum entropy modeling, and uses infinitely- weighted logistic regression for model fitting. The package is described in Vollering et al. (2019; <doi:10.1002/ece3.5654>).

Maintained by Julien Vollering. Last updated 7 months ago.

10.7 match 14 stars 6.53 score 30 scripts

bioc

SummarizedExperiment:A container (S4 class) for matrix-like assays

The SummarizedExperiment container contains one or more assays, each represented by a matrix-like object of numeric or other mode. The rows typically represent genomic ranges of interest and the columns represent samples.

Maintained by Hervé Pagès. Last updated 5 months ago.

genetics infrastructure sequencing annotation coverage genomeannotation bioconductor-package core-package

4.1 match 34 stars 16.85 score 8.6k scripts 1.2k dependents

r-forge

deSolve:Solvers for Initial Value Problems of Differential Equations ('ODE', 'DAE', 'DDE')

Functions that solve initial value problems of a system of first-order ordinary differential equations ('ODE'), of partial differential equations ('PDE'), of differential algebraic equations ('DAE'), and of delay differential equations. The functions provide an interface to the FORTRAN functions 'lsoda', 'lsodar', 'lsode', 'lsodes' of the 'ODEPACK' collection, to the FORTRAN functions 'dvode', 'zvode' and 'daspk' and a C-implementation of solvers of the 'Runge-Kutta' family with fixed or variable time steps. The package contains routines designed for solving 'ODEs' resulting from 1-D, 2-D and 3-D partial differential equations ('PDE') that have been converted to 'ODEs' by numerical differencing.

Maintained by Thomas Petzoldt. Last updated 1 years ago.

fortran openblas

5.3 match 12.33 score 8.0k scripts 427 dependents

astamm

nloptr:R Interface to NLopt

Solve optimization problems using an R interface to NLopt. NLopt is a free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines available online as well as original implementations of various other algorithms. See <https://nlopt.readthedocs.io/en/latest/NLopt_Algorithms/> for more information on the available algorithms. Building from included sources requires 'CMake'. On Linux and 'macOS', if a suitable system build of NLopt (2.7.0 or later) is found, it is used; otherwise, it is built from included sources via 'CMake'. On Windows, NLopt is obtained through 'rwinlib' for 'R <= 4.1.x' or grabbed from the appropriate toolchain for 'R >= 4.2.0'.

Maintained by Aymeric Stamm. Last updated 14 hours ago.

cpp

3.8 match 108 stars 17.13 score 1.1k scripts 1.8k dependents

bioc

beer:Bayesian Enrichment Estimation in R

BEER implements a Bayesian model for analyzing phage-immunoprecipitation sequencing (PhIP-seq) data. Given a PhIPData object, BEER returns posterior probabilities of enriched antibody responses, point estimates for the relative fold-change in comparison to negative control samples, and more. Additionally, BEER provides a convenient implementation for using edgeR to identify enriched antibody responses.

Maintained by Athena Chen. Last updated 5 months ago.

software statisticalmethod bayesian sequencing coverage jags cpp

11.9 match 10 stars 5.38 score 12 scripts

rvaradhan

dfoptim:Derivative-Free Optimization

Derivative-Free optimization algorithms. These algorithms do not require gradient information. More importantly, they can be used to solve non-smooth optimization problems.

Maintained by Ravi Varadhan. Last updated 2 years ago.

11.0 match 5.78 score 195 scripts 20 dependents

apariciojohan

flexFitR:Flexible Non-Linear Least Square Model Fitting

Provides tools for flexible non-linear least squares model fitting using general-purpose optimization techniques. The package supports a variety of optimization algorithms, including those provided by the 'optimx' package, making it suitable for handling complex non-linear models. Features include parallel processing support via the 'future' and 'foreach' packages, comprehensive model diagnostics, and visualization capabilities. Implements methods described in Nash and Varadhan (2011, <doi:10.18637/jss.v043.i09>).

Maintained by Johan Aparicio. Last updated 9 days ago.

nls optimization

8.8 match 2 stars 7.09 score 77 scripts

adamkocsis

via:Virtual Arrays

The base class 'VirtualArray' is defined, which acts as a wrapper around lists allowing users to fold arbitrary sequential data into n-dimensional, R-style virtual arrays. The derived 'XArray' class is defined to be used for homogeneous lists that contain a single class of objects. The 'RasterArray' and 'SfArray' classes enable the use of stacked spatial data instead of lists.

Maintained by Adam T. Kocsis. Last updated 2 years ago.

19.7 match 3 stars 3.18 score 8 scripts

moviedo5

fda.usc:Functional Data Analysis and Utilities for Statistical Computing

Routines for exploratory and descriptive analysis of functional data such as depth measurements, atypical curves detection, regression models, supervised classification, unsupervised classification and functional analysis of variance.

Maintained by Manuel Oviedo de la Fuente. Last updated 4 months ago.

functional-data-analysis fortran

6.3 match 12 stars 9.72 score 560 scripts 22 dependents

open-aims

bayesnec:A Bayesian No-Effect- Concentration (NEC) Algorithm

Implementation of No-Effect-Concentration estimation that uses 'brms' (see Burkner (2017)<doi:10.18637/jss.v080.i01>; Burkner (2018)<doi:10.32614/RJ-2018-017>; Carpenter 'et al.' (2017)<doi:10.18637/jss.v076.i01> to fit concentration(dose)-response data using Bayesian methods for the purpose of estimating 'ECx' values, but more particularly 'NEC' (see Fox (2010)<doi:10.1016/j.ecoenv.2009.09.012>), 'NSEC' (see Fisher and Fox (2023)<doi:10.1002/etc.5610>), and 'N(S)EC (see Fisher et al. 2023<doi:10.1002/ieam.4809>). A full description of this package can be found in Fisher 'et al.' (2024)<doi:10.18637/jss.v110.i05>. This package expands and supersedes an original version implemented in 'R2jags' (see Su and Yajima (2020)<https://CRAN.R-project.org/package=R2jags>; Fisher et al. (2020)<doi:10.5281/ZENODO.3966864>).

Maintained by Rebecca Fisher. Last updated 7 months ago.

bayesian-inference concentration-response ecotoxicology no-effect-concentration non-linear-decay threshold-derivation toxicology

7.5 match 12 stars 8.11 score 360 scripts

bioc

MAST:Model-based Analysis of Single Cell Transcriptomics

Methods and models for handling zero-inflated single cell assay data.

Maintained by Andrew McDavid. Last updated 5 months ago.

geneexpression differentialexpression genesetenrichment rnaseq transcriptomics singlecell

4.7 match 230 stars 12.75 score 1.8k scripts 5 dependents

santikka

causaleffect:Deriving Expressions of Joint Interventional Distributions and Transport Formulas in Causal Models

Functions for identification and transportation of causal effects. Provides a conditional causal effect identification algorithm (IDC) by Shpitser, I. and Pearl, J. (2006) <http://ftp.cs.ucla.edu/pub/stat_ser/r329-uai.pdf>, an algorithm for transportability from multiple domains with limited experiments by Bareinboim, E. and Pearl, J. (2014) <http://ftp.cs.ucla.edu/pub/stat_ser/r443.pdf>, and a selection bias recovery algorithm by Bareinboim, E. and Tian, J. (2015) <http://ftp.cs.ucla.edu/pub/stat_ser/r445.pdf>. All of the previously mentioned algorithms are based on a causal effect identification algorithm by Tian , J. (2002) <http://ftp.cs.ucla.edu/pub/stat_ser/r309.pdf>.

Maintained by Santtu Tikka. Last updated 2 years ago.

causal-inference causal-models causality-algorithms directed-acyclic-graph graphs identifiability identification igraph

11.1 match 29 stars 5.28 score 44 scripts 1 dependents

philchalmers

mirt:Multidimensional Item Response Theory

Analysis of discrete response data using unidimensional and multidimensional item analysis models under the Item Response Theory paradigm (Chalmers (2012) <doi:10.18637/jss.v048.i06>). Exploratory and confirmatory item factor analysis models are estimated with quadrature (EM) or stochastic (MHRM) methods. Confirmatory bi-factor and two-tier models are available for modeling item testlets using dimension reduction EM algorithms, while multiple group analyses and mixed effects designs are included for detecting differential item, bundle, and test functioning, and for modeling item and person covariates. Finally, latent class models such as the DINA, DINO, multidimensional latent class, mixture IRT models, and zero-inflated response models are supported, as well as a wide family of probabilistic unfolding models.

Maintained by Phil Chalmers. Last updated 11 days ago.

irt mirt openblas cpp openmp

3.8 match 210 stars 14.98 score 2.5k scripts 40 dependents

bquast

sigmoid:Sigmoid Functions for Machine Learning

Several different sigmoid functions are implemented, including a wrapper function, SoftMax preprocessing and inverse functions.

Maintained by Bastiaan Quast. Last updated 1 years ago.

9.0 match 2 stars 6.19 score 172 scripts 3 dependents

bioc

Biobase:Biobase: Base functions for Bioconductor

Functions that are needed by many other packages or which replace R functions.

Maintained by Bioconductor Package Maintainer. Last updated 5 months ago.

infrastructure bioconductor-package core-package

3.4 match 9 stars 16.45 score 6.6k scripts 1.8k dependents

pepkit

pepr:Reading Portable Encapsulated Projects

A PEP, or Portable Encapsulated Project, is a dataset that subscribes to the PEP structure for organizing metadata. It is written using a simple YAML + CSV format, it is your one-stop solution to metadata management across data analysis environments. This package reads this standardized project configuration structure into R. Described in Sheffield et al. (2021) <doi:10.1093/gigascience/giab077>.

Maintained by Nathan Sheffield. Last updated 1 years ago.

bioinformatics metadata

9.7 match 3 stars 5.62 score 20 scripts

big-life-lab

cchsflow:Transforming and Harmonizing CCHS Variables

Supporting the use of the Canadian Community Health Survey (CCHS) by transforming variables from each cycle into harmonized, consistent versions that span survey cycles (currently, 2001 to 2018). CCHS data used in this library is accessed and adapted in accordance to the Statistics Canada Open Licence Agreement. This package uses rec_with_table(), which was developed from 'sjmisc' rec(). Lüdecke D (2018). "sjmisc: Data and Variable Transformation Functions". Journal of Open Source Software, 3(26), 754. <doi:10.21105/joss.00754>.

Maintained by Kitty Chen. Last updated 1 years ago.

cchs opensci openscience

9.1 match 12 stars 6.02 score 192 scripts

jirotubuyaki

Jdmbs:Monte Carlo Option Pricing Algorithms for Jump Diffusion Models with Correlational Companies

Option is a one of the financial derivatives and its pricing is an important problem in practice. The process of stock prices are represented as Geometric Brownian motion [Black (1973) <doi:10.1086/260062>] or jump diffusion processes [Kou (2002) <doi:10.1287/mnsc.48.8.1086.166>]. In this package, algorithms and visualizations are implemented by Monte Carlo method in order to calculate European option price for three equations by Geometric Brownian motion and jump diffusion processes and furthermore a model that presents jumps among companies affect each other.

Maintained by Masashi Okada. Last updated 5 years ago.

black-scholes brownian-motion computational-finance derivatives finance financial-analysis financial-engineering jump-diffusion monte-carlo option option-pricing sde stochastic-differential-equations stochastic-processes stock-market

10.5 match 28 stars 5.15 score 6 scripts

lin-siting

ForLion:'ForLion' Algorithm to Find D-Optimal Designs for Experiments

Designing experimental plans that involve both discrete and continuous factors with general parametric statistical models using the 'ForLion' algorithm and 'EW ForLion' algorithm. The algorithms will search for locally optimal designs and EW optimal designs under the D-criterion. Reference: Huang, Y., Li, K., Mandal, A., & Yang, J., (2024)<doi:10.1007/s11222-024-10465-x>.

Maintained by Siting Lin. Last updated 1 months ago.

19.8 match 2.70 score

ropensci

rOPTRAM:Derive Soil Moisture Using the OPTRAM Algorithm

The OPtical TRapezoid Model (OPTRAM) derives soil moisture based on the linear relation between a vegetation index and Land Surface Temperature (LST). The Short Wave Infra-red (SWIR) band is used as a proxy for LST. See: Sadeghi, M. et al., 2017. <https://doi.org/10.1016/j.rse.2017.05.041> .

Maintained by Micha Silver. Last updated 1 months ago.

9.3 match 9 stars 5.73 score 6 scripts

jasjeetsekhon

rgenoud:R Version of GENetic Optimization Using Derivatives

A genetic algorithm plus derivative optimizer.

Maintained by Jasjeet Singh Sekhon. Last updated 2 years ago.

5.4 match 12 stars 9.76 score 251 scripts 29 dependents

choi-phd

TestDesign:Optimal Test Design Approach to Fixed and Adaptive Test Construction

Uses the optimal test design approach by Birnbaum (1968, ISBN:9781593119348) and van der Linden (2018) <doi:10.1201/9781315117430> to construct fixed, adaptive, and parallel tests. Supports the following mixed-integer programming (MIP) solver packages: 'Rsymphony', 'highs', 'gurobi', 'lpSolve', and 'Rglpk'. The 'gurobi' package is not available from CRAN; see <https://www.gurobi.com/downloads/>.

Maintained by Seung W. Choi. Last updated 6 months ago.

openblas cpp

7.1 match 3 stars 7.34 score 37 scripts 2 dependents

dkaschek

dMod:Dynamic Modeling and Parameter Estimation in ODE Models

The framework provides functions to generate ODEs of reaction networks, parameter transformations, observation functions, residual functions, etc. The framework follows the paradigm that derivative information should be used for optimization whenever possible. Therefore, all major functions produce and can handle expressions for symbolic derivatives.

Maintained by Daniel Kaschek. Last updated 10 days ago.

6.2 match 20 stars 8.35 score 251 scripts

bioc

doubletrouble:Identification and classification of duplicated genes

doubletrouble aims to identify duplicated genes from whole-genome protein sequences and classify them based on their modes of duplication. The duplication modes are i. segmental duplication (SD); ii. tandem duplication (TD); iii. proximal duplication (PD); iv. transposed duplication (TRD) and; v. dispersed duplication (DD). Transposon-derived duplicates (TRD) can be further subdivided into rTRD (retrotransposon-derived duplication) and dTRD (DNA transposon-derived duplication). If users want a simpler classification scheme, duplicates can also be classified into SD- and SSD-derived (small-scale duplication) gene pairs. Besides classifying gene pairs, users can also classify genes, so that each gene is assigned a unique mode of duplication. Users can also calculate substitution rates per substitution site (i.e., Ka and Ks) from duplicate pairs, find peaks in Ks distributions with Gaussian Mixture Models (GMMs), and classify gene pairs into age groups based on Ks peaks.

Maintained by Fabrício Almeida-Silva. Last updated 4 days ago.

software wholegenome comparativegenomics functionalgenomics phylogenetics network classification bioinformatics comparative-genomics gene-duplication molecular-evolution whole-genome-duplication

7.8 match 23 stars 6.44 score 17 scripts

insightsengineering

rbmi:Reference Based Multiple Imputation

Implements standard and reference based multiple imputation methods for continuous longitudinal endpoints (Gower-Page et al. (2022) <doi:10.21105/joss.04251>). In particular, this package supports deterministic conditional mean imputation and jackknifing as described in Wolbers et al. (2022) <doi:10.1002/pst.2234>, Bayesian multiple imputation as described in Carpenter et al. (2013) <doi:10.1080/10543406.2013.834911>, and bootstrapped maximum likelihood imputation as described in von Hippel and Bartlett (2021) <doi: 10.1214/20-STS793>.

Maintained by Isaac Gravestock. Last updated 24 days ago.

5.7 match 18 stars 8.78 score 33 scripts 1 dependents

pboutros

ISOpureR:Deconvolution of Tumour Profiles

Deconvolution of mixed tumour profiles into normal and cancer for each patient, using the ISOpure algorithm in Quon et al. Genome Medicine, 2013 5:29. Deconvolution requires mixed tumour profiles and a set of unmatched "basis" normal profiles.

Maintained by Paul C Boutros. Last updated 6 years ago.

cpp

13.6 match 3 stars 3.61 score 34 scripts

poissonconsulting

embr:Model Builder Utility Functions and Virtual Classes

Utility functions and virtual classes shared by model builder packages such as tmbr, jmbr and smbr.

Maintained by Joe Thorley. Last updated 1 months ago.

analyses mbr

10.5 match 3 stars 4.61 score 4 scripts 3 dependents

dankelley

oce:Analysis of Oceanographic Data

Supports the analysis of Oceanographic data, including 'ADCP' measurements, measurements made with 'argo' floats, 'CTD' measurements, sectional data, sea-level time series, coastline and topographic data, etc. Provides specialized functions for calculating seawater properties such as potential temperature in either the 'UNESCO' or 'TEOS-10' equation of state. Produces graphical displays that conform to the conventions of the Oceanographic literature. This package is discussed extensively by Kelley (2018) "Oceanographic Analysis with R" <doi:10.1007/978-1-4939-8844-0>.

Maintained by Dan Kelley. Last updated 2 days ago.

oceanography fortran cpp

3.1 match 146 stars 15.42 score 4.2k scripts 18 dependents

bioc

mixOmics:Omics Data Integration Project

Multivariate methods are well suited to large omics data sets where the number of variables (e.g. genes, proteins, metabolites) is much larger than the number of samples (patients, cells, mice). They have the appealing properties of reducing the dimension of the data by using instrumental variables (components), which are defined as combinations of all variables. Those components are then used to produce useful graphical outputs that enable better understanding of the relationships and correlation structures between the different data sets that are integrated. mixOmics offers a wide range of multivariate methods for the exploration and integration of biological datasets with a particular focus on variable selection. The package proposes several sparse multivariate models we have developed to identify the key variables that are highly correlated, and/or explain the biological outcome of interest. The data that can be analysed with mixOmics may come from high throughput sequencing technologies, such as omics data (transcriptomics, metabolomics, proteomics, metagenomics etc) but also beyond the realm of omics (e.g. spectral imaging). The methods implemented in mixOmics can also handle missing values without having to delete entire rows with missing data. A non exhaustive list of methods include variants of generalised Canonical Correlation Analysis, sparse Partial Least Squares and sparse Discriminant Analysis. Recently we implemented integrative methods to combine multiple data sets: N-integration with variants of Generalised Canonical Correlation Analysis and P-integration with variants of multi-group Partial Least Squares.

Maintained by Eva Hamrud. Last updated 4 days ago.

immunooncology microarray sequencing metabolomics metagenomics proteomics geneprediction multiplecomparison classification regression bioconductor genomics genomics-data genomics-visualization multivariate-analysis multivariate-statistics omics r-pkg r-project

3.5 match 182 stars 13.71 score 1.3k scripts 22 dependents

pyfe

FER:Financial Engineering in R

R implementations of standard financial engineering codes; vanilla option pricing models such as Black-Scholes, Bachelier, CEV, and SABR.

Maintained by Jaehyuk Choi. Last updated 4 years ago.

bachelier black-scholes derivatives financial-engineering mathematical-finance option-pricing quantitative-finance

10.0 match 12 stars 4.76 score 12 scripts

friendly

HistData:Data Sets from the History of Statistics and Data Visualization

The 'HistData' package provides a collection of small data sets that are interesting and important in the history of statistics and data visualization. The goal of the package is to make these available, both for instructional use and for historical research. Some of these present interesting challenges for graphics or analysis in R.

Maintained by Michael Friendly. Last updated 10 months ago.

graphics historical-data

5.1 match 63 stars 9.19 score 732 scripts 2 dependents

smwindecker

mixchar:Mixture Model for the Deconvolution of Thermal Decay Curves

Deconvolution of thermal decay curves allows you to quantify proportions of biomass components in plant litter. Thermal decay curves derived from thermogravimetric analysis (TGA) are imported, modified, and then modelled in a three- or four- part mixture model using the Fraser-Suzuki function. The output is estimates for weights of pseudo-components corresponding to hemicellulose, cellulose, and lignin. For more information see: Müller-Hagedorn, M. and Bockhorn, H. (2007) <doi:10.1016/j.jaap.2006.12.008>, Órfão, J. J. M. and Figueiredo, J. L. (2001) <doi:10.1016/S0040-6031(01)00634-7>, and Yang, H. and Yan, R. and Chen, H. and Zheng, C. and Lee, D. H. and Liang, D. T. (2006) <doi:10.1021/ef0580117>.

Maintained by Saras Windecker. Last updated 2 years ago.

decay thermogravimetry traits

9.0 match 10 stars 5.26 score 18 scripts

jarrodhadfield

MCMCglmm:MCMC Generalised Linear Mixed Models

Fits Multivariate Generalised Linear Mixed Models (and related models) using Markov chain Monte Carlo techniques (Hadfield 2010 J. Stat. Soft.).

Maintained by Jarrod Hadfield. Last updated 3 months ago.

cpp

5.3 match 2 stars 8.83 score 1.2k scripts 13 dependents

ropensci

datapack:A Flexible Container to Transport and Manipulate Data and Associated Resources

Provides a flexible container to transport and manipulate complex sets of data. These data may consist of multiple data files and associated meta data and ancillary files. Individual data objects have associated system level meta data, and data files are linked together using the OAI-ORE standard resource map which describes the relationships between the files. The OAI- ORE standard is described at <https://www.openarchives.org/ore/>. Data packages can be serialized and transported as structured files that have been created following the BagIt specification. The BagIt specification is described at <https://tools.ietf.org/html/draft-kunze-bagit-08>.

Maintained by Matthew B. Jones. Last updated 3 years ago.

5.4 match 44 stars 8.56 score 195 scripts 4 dependents

wlenhard

cNORM:Continuous Norming

A comprehensive toolkit for generating continuous test norms in psychometrics and biometrics, and analyzing model fit. The package offers both distribution-free modeling using Taylor polynomials and parametric modeling using the beta-binomial distribution. Originally developed for achievement tests, it is applicable to a wide range of mental, physical, or other test scores dependent on continuous or discrete explanatory variables. The package provides several advantages: It minimizes deviations from representativeness in subsamples, interpolates between discrete levels of explanatory variables, and significantly reduces the required sample size compared to conventional norming per age group. cNORM enables graphical and analytical evaluation of model fit, accommodates a wide range of scales including those with negative and descending values, and even supports conventional norming. It generates norm tables including confidence intervals. It also includes methods for addressing representativeness issues through Iterative Proportional Fitting.

Maintained by Wolfgang Lenhard. Last updated 4 months ago.

beta-binomial biometrics continuous-norming growth-curve norm-scores norm-tables normalization-techniques percentile psychometrics regression-based-norming taylor-series

8.4 match 2 stars 5.49 score 75 scripts

gamlss-dev

gamlss:Generalized Additive Models for Location Scale and Shape

Functions for fitting the Generalized Additive Models for Location Scale and Shape introduced by Rigby and Stasinopoulos (2005), <doi:10.1111/j.1467-9876.2005.00510.x>. The models use a distributional regression approach where all the parameters of the conditional distribution of the response variable are modelled using explanatory variables.

Maintained by Mikis Stasinopoulos. Last updated 4 months ago.

4.0 match 16 stars 11.23 score 2.0k scripts 49 dependents

polinasuter

BiDAG:Bayesian Inference for Directed Acyclic Graphs

Implementation of a collection of MCMC methods for Bayesian structure learning of directed acyclic graphs (DAGs), both from continuous and discrete data. For efficient inference on larger DAGs, the space of DAGs is pruned according to the data. To filter the search space, the algorithm employs a hybrid approach, combining constraint-based learning with search and score. A reduced search space is initially defined on the basis of a skeleton obtained by means of the PC-algorithm, and then iteratively improved with search and score. Search and score is then performed following two approaches: Order MCMC, or Partition MCMC. The BGe score is implemented for continuous data and the BDe score is implemented for binary data or categorical data. The algorithms may provide the maximum a posteriori (MAP) graph or a sample (a collection of DAGs) from the posterior distribution given the data. All algorithms are also applicable for structure learning and sampling for dynamic Bayesian networks. References: J. Kuipers, P. Suter, G. Moffa (2022) <doi:10.1080/10618600.2021.2020127>, N. Friedman and D. Koller (2003) <doi:10.1023/A:1020249912095>, J. Kuipers and G. Moffa (2017) <doi:10.1080/01621459.2015.1133426>, M. Kalisch et al. (2012) <doi:10.18637/jss.v047.i11>, D. Geiger and D. Heckerman (2002) <doi:10.1214/aos/1035844981>, P. Suter, J. Kuipers, G. Moffa, N.Beerenwinkel (2023) <doi:10.18637/jss.v105.i09>.

Maintained by Polina Suter. Last updated 2 years ago.

cpp

13.6 match 4 stars 3.29 score 81 scripts 2 dependents

albgarre

bioinactivation:Mathematical Modelling of (Dynamic) Microbial Inactivation

Functions for modelling microbial inactivation under isothermal or dynamic conditions. The calculations are based on several mathematical models broadly used by the scientific community and industry. Functions enable to make predictions for cases where the kinetic parameters are known. It also implements functions for parameter estimation for isothermal and dynamic conditions. The model fitting capabilities include an Adaptive Monte Carlo method for a Bayesian approach to parameter estimation.

Maintained by Alberto Garre. Last updated 2 years ago.

food food-safety inactivation-models isothermal-experiments prediction

11.0 match 3.95 score 18 scripts

cristianetaniguti

onemap:Construction of Genetic Maps in Experimental Crosses

Analysis of molecular marker data from model (backcrosses, F2 and recombinant inbred lines) and non-model systems (i. e. outcrossing species). For the later, it allows statistical analysis by simultaneously estimating linkage and linkage phases (genetic map construction) according to Wu et al. (2002) <doi:10.1006/tpbi.2002.1577>. All analysis are based on multipoint approaches using hidden Markov models.

Maintained by Cristiane Taniguti. Last updated 2 months ago.

cpp

6.6 match 3 stars 6.58 score 183 scripts

mjockers

syuzhet:Extracts Sentiment and Sentiment-Derived Plot Arcs from Text

Extracts sentiment and sentiment-derived plot arcs from text using a variety of sentiment dictionaries conveniently packaged for consumption by R users. Implemented dictionaries include "syuzhet" (default) developed in the Nebraska Literary Lab "afinn" developed by Finn Årup Nielsen, "bing" developed by Minqing Hu and Bing Liu, and "nrc" developed by Mohammad, Saif M. and Turney, Peter D. Applicable references are available in README.md and in the documentation for the "get_sentiment" function. The package also provides a hack for implementing Stanford's coreNLP sentiment parser. The package provides several methods for plot arc normalization.

Maintained by Matthew Jockers. Last updated 2 years ago.

3.4 match 336 stars 12.92 score 1.4k scripts 31 dependents

matthieu-bruneaux

isotracer:Isotopic Tracer Analysis Using MCMC

Implements Bayesian models to analyze data from tracer addition experiments. The implemented method was originally described in the article "A New Method to Reconstruct Quantitative Food Webs and Nutrient Flows from Isotope Tracer Addition Experiments" by López-Sepulcre et al. (2020) <doi:10.1086/708546>.

Maintained by Matthieu Bruneaux. Last updated 4 months ago.

cpp

7.3 match 5.92 score 60 scripts

mattmar

dynamAedes:A Unified Mechanistic Model for the Population Dynamics of Invasive Aedes Mosquitoes

Generalised model for population dynamics of invasive Aedes mosquitoes. Rationale and model structure are described here: Da Re et al. (2021) <doi:10.1016/j.ecoinf.2020.101180> and Da Re et al. (2022) <doi:10.1101/2021.12.21.473628>.

Maintained by Matteo Marcantonio. Last updated 1 years ago.

ecology invasive-species modelling mosquitoes pathogens

7.8 match 7 stars 5.59 score 11 scripts

murrayefford

openCR:Open Population Capture-Recapture

Non-spatial and spatial open-population capture-recapture analysis.

Maintained by Murray Efford. Last updated 5 months ago.

cpp

7.3 match 4 stars 5.98 score 53 scripts

jaipizgon

NeuralSens:Sensitivity Analysis of Neural Networks

Analysis functions to quantify inputs importance in neural network models. Functions are available for calculating and plotting the inputs importance and obtaining the activation function of each neuron layer and its derivatives. The importance of a given input is defined as the distribution of the derivatives of the output with respect to that input in each training data point <doi:10.18637/jss.v102.i07>.

Maintained by Jaime Pizarroso Gonzalo. Last updated 6 months ago.

8.0 match 15 stars 5.43 score 24 scripts

ericgiunta

Colossus:"Risk Model Regression and Analysis with Complex Non-Linear Models"

Performs survival analysis using general non-linear models. Risk models can be the sum or product of terms. Each term is the product of exponential/linear functions of covariates. Additionally sub-terms can be defined as a sum of exponential, linear threshold, and step functions. Cox Proportional hazards <https://en.wikipedia.org/wiki/Proportional_hazards_model>, Poisson <https://en.wikipedia.org/wiki/Poisson_regression>, and Fine-Gray competing risks <https://www.publichealth.columbia.edu/research/population-health-methods/competing-risk-analysis> regression are supported. This work was sponsored by NASA Grant 80NSSC19M0161 through a subcontract from the National Council on Radiation Protection and Measurements (NCRP). The computing for this project was performed on the Beocat Research Cluster at Kansas State University, which is funded in part by NSF grants CNS-1006860, EPS-1006860, EPS-0919443, ACI-1440548, CHE-1726332, and NIH P20GM113109.

Maintained by Eric Giunta. Last updated 3 days ago.

cpp openmp

6.1 match 1 stars 7.06 score 36 scripts

bioc

satuRn:Scalable Analysis of Differential Transcript Usage for Bulk and Single-Cell RNA-sequencing Applications

satuRn provides a higly performant and scalable framework for performing differential transcript usage analyses. The package consists of three main functions. The first function, fitDTU, fits quasi-binomial generalized linear models that model transcript usage in different groups of interest. The second function, testDTU, tests for differential usage of transcripts between groups of interest. Finally, plotDTU visualizes the usage profiles of transcripts in groups of interest.

Maintained by Jeroen Gilis. Last updated 5 months ago.

regression experimentaldesign differentialexpression geneexpression rnaseq sequencing software singlecell transcriptomics multiplecomparison visualization

6.1 match 21 stars 6.97 score 74 scripts 1 dependents

tmsalab

edmdata:Data Sets for Psychometric Modeling

Collection of data sets from various assessments that can be used to evaluate psychometric models. These data sets have been analyzed in the following papers that introduced new methodology as part of the application section: Jimenez, A., Balamuta, J. J., & Culpepper, S. A. (2023) <doi:10.1111/bmsp.12307>, Culpepper, S. A., & Balamuta, J. J. (2021) <doi:10.1080/00273171.2021.1985949>, Yinghan Chen et al. (2021) <doi:10.1007/s11336-021-09750-9>, Yinyin Chen et al. (2020) <doi:10.1007/s11336-019-09693-2>, Culpepper, S. A. (2019a) <doi:10.1007/s11336-019-09683-4>, Culpepper, S. A. (2019b) <doi:10.1007/s11336-018-9643-8>, Culpepper, S. A., & Chen, Y. (2019) <doi:10.3102/1076998618791306>, Culpepper, S. A., & Balamuta, J. J. (2017) <doi:10.1007/s11336-015-9484-7>, and Culpepper, S. A. (2015) <doi:10.3102/1076998615595403>.

Maintained by James Joseph Balamuta. Last updated 6 months ago.

cognitive-diagnostic-models data edm

10.1 match 5 stars 4.18 score 7 scripts 1 dependents

spatstat

spatstat.explore:Exploratory Data Analysis for the 'spatstat' Family

Functionality for exploratory data analysis and nonparametric analysis of spatial data, mainly spatial point patterns, in the 'spatstat' family of packages. (Excludes analysis of spatial data on a linear network, which is covered by the separate package 'spatstat.linnet'.) Methods include quadrat counts, K-functions and their simulation envelopes, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated bandwidth selection, mark correlation functions, segregation indices, mark dependence diagnostics, and kernel estimates of covariate effects. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two-stage Monte Carlo) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov, ANOVA) are also supported.

Maintained by Adrian Baddeley. Last updated 1 months ago.

cluster-detection confidence-intervals hypothesis-testing k-function roc-curves scan-statistics significance-testing simulation-envelopes spatial-analysis spatial-data-analysis spatial-sharpening spatial-smoothing spatial-statistics

4.1 match 1 stars 10.17 score 67 scripts 148 dependents

r-forge

minqa:Derivative-Free Optimization Algorithms by Quadratic Approximation

Derivative-free optimization by quadratic approximation based on an interface to Fortran implementations by M. J. D. Powell.

Maintained by Katharine M. Mullen. Last updated 2 months ago.

fortran cpp

3.5 match 1 stars 11.73 score 227 scripts 1.7k dependents

ovvo-financial

NNS:Nonlinear Nonparametric Statistics

Nonlinear nonparametric statistics using partial moments. Partial moments are the elements of variance and asymptotically approximate the area of f(x). These robust statistics provide the basis for nonlinear analysis while retaining linear equivalences. NNS offers: Numerical integration, Numerical differentiation, Clustering, Correlation, Dependence, Causal analysis, ANOVA, Regression, Classification, Seasonality, Autoregressive modeling, Normalization, Stochastic dominance and Advanced Monte Carlo sampling. All routines based on: Viole, F. and Nawrocki, D. (2013), Nonlinear Nonparametric Statistics: Using Partial Moments (ISBN: 1490523995).

Maintained by Fred Viole. Last updated 5 days ago.

clustering econometrics machine-learning nonlinear nonparametric partial-moments statistics time-series cpp

3.7 match 71 stars 10.96 score 66 scripts 3 dependents

bioc

netZooR:Unified methods for the inference and analysis of gene regulatory networks

netZooR unifies the implementations of several Network Zoo methods (netzoo, netzoo.github.io) into a single package by creating interfaces between network inference and network analysis methods. Currently, the package has 3 methods for network inference including PANDA and its optimized implementation OTTER (network reconstruction using mutliple lines of biological evidence), LIONESS (single-sample network inference), and EGRET (genotype-specific networks). Network analysis methods include CONDOR (community detection), ALPACA (differential community detection), CRANE (significance estimation of differential modules), MONSTER (estimation of network transition states). In addition, YARN allows to process gene expresssion data for tissue-specific analyses and SAMBAR infers missing mutation data based on pathway information.

Maintained by Tara Eicher. Last updated 9 days ago.

networkinference network generegulation geneexpression transcription microarray graphandnetwork gene-regulatory-network transcription-factors

5.0 match 105 stars 7.98 score

smac-group

simts:Time Series Analysis Tools

A system contains easy-to-use tools as a support for time series analysis courses. In particular, it incorporates a technique called Generalized Method of Wavelet Moments (GMWM) as well as its robust implementation for fast and robust parameter estimation of time series models which is described, for example, in Guerrier et al. (2013) <doi: 10.1080/01621459.2013.799920>. More details can also be found in the paper linked to via the URL below.

Maintained by Stéphane Guerrier. Last updated 2 years ago.

rcpp rcpparmadillo simulation time-series timeseries timeseries-data openblas cpp

5.2 match 15 stars 7.68 score 59 scripts 4 dependents

vivianephilipps

marqLevAlg:A Parallelized General-Purpose Optimization Based on Marquardt-Levenberg Algorithm

This algorithm provides a numerical solution to the problem of unconstrained local minimization (or maximization). It is particularly suited for complex problems and more efficient than the Gauss-Newton-like algorithm when starting from points very far from the final minimum (or maximum). Each iteration is parallelized and convergence relies on a stringent stopping criterion based on the first and second derivatives. See Philipps et al, 2021 <doi:10.32614/RJ-2021-089>.

Maintained by Viviane Philipps. Last updated 1 years ago.

fortran

6.1 match 7 stars 6.52 score 12 scripts 10 dependents

marjoleinf

pre:Prediction Rule Ensembles

Derives prediction rule ensembles (PREs). Largely follows the procedure for deriving PREs as described in Friedman & Popescu (2008; <DOI:10.1214/07-AOAS148>), with adjustments and improvements. The main function pre() derives prediction rule ensembles consisting of rules and/or linear terms for continuous, binary, count, multinomial, and multivariate continuous responses. Function gpe() derives generalized prediction ensembles, consisting of rules, hinge and linear functions of the predictor variables.

Maintained by Marjolein Fokkema. Last updated 9 months ago.

4.7 match 58 stars 8.49 score 98 scripts 1 dependents

robinhankin

elliptic:Weierstrass and Jacobi Elliptic Functions

A suite of elliptic and related functions including Weierstrass and Jacobi forms. Also includes various tools for manipulating and visualizing complex functions.

Maintained by Robin K. S. Hankin. Last updated 12 days ago.

4.3 match 3 stars 9.31 score 54 scripts 79 dependents

r-cas

Ryacas:R Interface to the 'Yacas' Computer Algebra System

Interface to the 'yacas' computer algebra system (<http://www.yacas.org/>).

Maintained by Mikkel Meyer Andersen. Last updated 2 years ago.

cpp

3.9 match 40 stars 10.15 score 167 scripts 14 dependents

robinhankin

freealg:The Free Algebra

The free algebra in R with non-commuting indeterminates. Uses 'disordR' discipline (Hankin, 2022, <doi:10.48550/ARXIV.2210.03856>). To cite the package in publications please use Hankin (2022) <doi:10.48550/ARXIV.2211.04002>.

Maintained by Robin K. S. Hankin. Last updated 5 days ago.

cpp

5.6 match 3 stars 7.07 score 10 dependents

nago2020

depCensoring:Statistical Methods for Survival Data with Dependent Censoring

Several statistical methods for analyzing survival data under various forms of dependent censoring are implemented in the package. In addition to accounting for dependent censoring, it offers tools to adjust for unmeasured confounding factors. The implemented approaches allow users to estimate the dependency between survival time and dependent censoring time, based solely on observed survival data. For more details on the methods, refer to Deresa and Van Keilegom (2021) <doi:10.1093/biomet/asaa095>, Czado and Van Keilegom (2023) <doi:10.1093/biomet/asac067>, Crommen et al. (2024) <doi:10.1007/s11749-023-00903-9>, Deresa and Van Keilegom (2024) <doi:10.1080/01621459.2022.2161387>, Rutten et al. (2024+) <doi:10.48550/arXiv.2403.11860> and Ding and Van Keilegom (2024).

Maintained by Negera Wakgari Deresa. Last updated 11 days ago.

14.1 match 2.78 score 5 scripts

inlabru-org

inlabru:Bayesian Latent Gaussian Modelling using INLA and Extensions

Facilitates spatial and general latent Gaussian modeling using integrated nested Laplace approximation via the INLA package (<https://www.r-inla.org>). Additionally, extends the GAM-like model class to more general nonlinear predictor expressions, and implements a log Gaussian Cox process likelihood for modeling univariate and spatial point processes based on ecological survey data. Model components are specified with general inputs and mapping methods to the latent variables, and the predictors are specified via general R expressions, with separate expressions for each observation likelihood model in multi-likelihood models. A prediction method based on fast Monte Carlo sampling allows posterior prediction of general expressions of the latent variables. Ecology-focused introduction in Bachl, Lindgren, Borchers, and Illian (2019) <doi:10.1111/2041-210X.13168>.

Maintained by Finn Lindgren. Last updated 4 days ago.

3.1 match 96 stars 12.62 score 832 scripts 6 dependents

niaid

dsb:Normalize & Denoise Droplet Single Cell Protein Data (CITE-Seq)

This lightweight R package provides a method for normalizing and denoising protein expression data from droplet based single cell experiments. Raw protein Unique Molecular Index (UMI) counts from sequencing DNA-conjugated antibody derived tags (ADT) in droplets (e.g. 'CITE-seq') have substantial measurement noise. Our experiments and computational modeling revealed two major components of this noise: 1) protein-specific noise originating from ambient, unbound antibody encapsulated in droplets that can be accurately inferred via the expected protein counts detected in empty droplets, and 2) droplet/cell-specific noise revealed via the shared variance component associated with isotype antibody controls and background protein counts in each cell. This package normalizes and removes both of these sources of noise from raw protein data derived from methods such as 'CITE-seq', 'REAP-seq', 'ASAP-seq', 'TEA-seq', 'proteogenomic' data from the Mission Bio platform, etc. See the vignette for tutorials on how to integrate dsb with 'Seurat' and 'Bioconductor' and how to use dsb in 'Python'. Please see our paper Mulè M.P., Martins A.J., and Tsang J.S. Nature Communications 2022 <https://www.nature.com/articles/s41467-022-29356-8> for more details on the method.

Maintained by Matthew Mulè. Last updated 9 months ago.

cite-seq niaid-tsang-lab

5.0 match 65 stars 7.73 score 104 scripts

aphalo

photobiology:Photobiological Calculations

Definitions of classes, methods, operators and functions for use in photobiology and radiation meteorology and climatology. Calculation of effective (weighted) and not-weighted irradiances/doses, fluence rates, transmittance, reflectance, absorptance, absorbance and diverse ratios and other derived quantities from spectral data. Local maxima and minima: peaks, valleys and spikes. Conversion between energy-and photon-based units. Wavelength interpolation. Astronomical calculations related solar angles and day length. Colours and vision. This package is part of the 'r4photobiology' suite, Aphalo, P. J. (2015) <doi:10.19232/uv4pb.2015.1.14>.

Maintained by Pedro J. Aphalo. Last updated 3 days ago.

light photobiology quantification r4photobiology-suite radiation spectra sun-position

4.1 match 4 stars 9.35 score 604 scripts 12 dependents

davidnsousa

qsort:Scoring Q-Sort Data

Computes scores from Q-sort data, using criteria sorts and derived scales from subsets of items. The 'qsort' package includes descriptions and scoring procedures for four different Q-sets commonly used in developmental psychology research: Attachment Q-set (version 3.0) (Waters, 1995, <doi:10.1111/j.1540-5834.1995.tb00214.x>); California Child Q-set (Block and Block, 1969, <doi:10.1037/0012-1649.21.3.508>); Maternal Behaviour Q-set (version 3.1) (Pederson et al., 1999, <https://ir.lib.uwo.ca/cgi/viewcontent.cgi?article=1000&context=psychologypub>); Preschool Q-set (Baumrind, 1968 revised by Wanda Bronson, <doi:10.1111/j.1540-5834.1995.tb00214.x>).

Maintained by David N Sousa. Last updated 6 years ago.

14.2 match 2.70 score 8 scripts

msalibian

RobStatTM:Robust Statistics: Theory and Methods

Companion package for the book: "Robust Statistics: Theory and Methods, second edition", <http://www.wiley.com/go/maronna/robust>. This package contains code that implements the robust estimators discussed in the recent second edition of the book above, as well as the scripts reproducing all the examples in the book.

Maintained by Matias Salibian-Barrera. Last updated 3 days ago.

robust robust-estimation robust-regression robust-statistics robustness statistics fortran openblas

3.8 match 17 stars 10.23 score 84 scripts 8 dependents

alexisderumigny

ElliptCopulas:Inference of Elliptical Distributions and Copulas

Provides functions for the simulation and the nonparametric estimation of elliptical distributions, meta-elliptical copulas and trans-elliptical distributions, following the article Derumigny and Fermanian (2022) <doi:10.1016/j.jmva.2022.104962>.

Maintained by Alexis Derumigny. Last updated 6 months ago.

copula elliptical-copula elliptical-distribution r-pkg

8.8 match 4 stars 4.38 score 2 scripts 1 dependents

d-acharya

Dowd:Functions Ported from 'MMR2' Toolbox Offered in Kevin Dowd's Book Measuring Market Risk

'Kevin Dowd's' book Measuring Market Risk is a widely read book in the area of risk measurement by students and practitioners alike. As he claims, 'MATLAB' indeed might have been the most suitable language when he originally wrote the functions, but, with growing popularity of R it is not entirely valid. As 'Dowd's' code was not intended to be error free and were mainly for reference, some functions in this package have inherited those errors. An attempt will be made in future releases to identify and correct them. 'Dowd's' original code can be downloaded from www.kevindowd.org/measuring-market-risk/. It should be noted that 'Dowd' offers both 'MMR2' and 'MMR1' toolboxes. Only 'MMR2' was ported to R. 'MMR2' is more recent version of 'MMR1' toolbox and they both have mostly similar function. The toolbox mainly contains different parametric and non parametric methods for measurement of market risk as well as backtesting risk measurement methods.

Maintained by Dinesh Acharya. Last updated 9 years ago.

11.9 match 3.19 score 154 scripts

robinhankin

mvp:Fast Symbolic Multivariate Polynomials

Fast manipulation of symbolic multivariate polynomials using the 'Map' class of the Standard Template Library. The package uses print and coercion methods from the 'mpoly' package but offers speed improvements. It is comparable in speed to the 'spray' package for sparse arrays, but retains the symbolic benefits of 'mpoly'. To cite the package in publications, use Hankin 2022 <doi:10.48550/ARXIV.2210.15991>. Uses 'disordR' discipline.

Maintained by Robin K. S. Hankin. Last updated 4 days ago.

cpp

5.6 match 9 stars 6.83 score 36 scripts 2 dependents

robinhankin

spray:Sparse Arrays and Multivariate Polynomials

Sparse arrays interpreted as multivariate polynomials. Uses 'disordR' discipline (Hankin, 2022, <doi:10.48550/ARXIV.2210.03856>). To cite the package in publications please use Hankin (2022) <doi:10.48550/ARXIV.2210.10848>.

Maintained by Robin K. S. Hankin. Last updated 2 months ago.

cpp

5.6 match 2 stars 6.62 score 35 scripts 4 dependents

mmaechler

sfsmisc:Utilities from 'Seminar fuer Statistik' ETH Zurich

Useful utilities ['goodies'] from Seminar fuer Statistik ETH Zurich, some of which were ported from S-plus in the 1990s. For graphics, have pretty (Log-scale) axes eaxis(), an enhanced Tukey-Anscombe plot, combining histogram and boxplot, 2d-residual plots, a 'tachoPlot()', pretty arrows, etc. For robustness, have a robust F test and robust range(). For system support, notably on Linux, provides 'Sys.*()' functions with more access to system and CPU information. Finally, miscellaneous utilities such as simple efficient prime numbers, integer codes, Duplicated(), toLatex.numeric() and is.whole().

Maintained by Martin Maechler. Last updated 5 months ago.

3.4 match 11 stars 10.87 score 566 scripts 119 dependents

nctingwang

merDeriv:Case-Wise and Cluster-Wise Derivatives for Mixed Effects Models

Compute case-wise and cluster-wise derivative for mixed effects models with respect to fixed effects parameter, random effect (co)variances, and residual variance. This material is partially based on work supported by the National Science Foundation under Grant Number 1460719.

Maintained by Ting Wang. Last updated 3 years ago.

6.6 match 3 stars 5.45 score 71 scripts 2 dependents

ikosmidis

enrichwith:Methods to Enrich R Objects with Extra Components

Provides the "enrich" method to enrich list-like R objects with new, relevant components. The current version has methods for enriching objects of class 'family', 'link-glm', 'lm', 'glm' and 'betareg'. The resulting objects preserve their class, so all methods associated with them still apply. The package also provides the 'enriched_glm' function that has the same interface as 'glm' but results in objects of class 'enriched_glm'. In addition to the usual components in a `glm` object, 'enriched_glm' objects carry an object-specific simulate method and functions to compute the scores, the observed and expected information matrix, the first-order bias, as well as model densities, probabilities, and quantiles at arbitrary parameter values. The package can also be used to produce customizable source code templates for the structured implementation of methods to compute new components and enrich arbitrary objects.

Maintained by Ioannis Kosmidis. Last updated 5 years ago.

infrastructure

4.8 match 6 stars 7.35 score 16 scripts 12 dependents

yihui

knitr:A General-Purpose Package for Dynamic Report Generation in R

Provides a general-purpose tool for dynamic report generation in R using Literate Programming techniques.

Maintained by Yihui Xie. Last updated 4 hours ago.

dynamic-documents knitr literate-programming rmarkdown sweave

1.5 match 2.4k stars 23.61 score 116k scripts 4.2k dependents

paulgovan

AutoDeskR:An Interface to the 'AutoDesk' 'API' Platform

An interface to the 'AutoDesk' 'API' Platform including the Authentication 'API' for obtaining authentication to the 'AutoDesk' Forge Platform, Data Management 'API' for managing data across the platform's cloud services, Design Automation 'API' for performing automated tasks on design files in the cloud, Model Derivative 'API' for translating design files into different formats, sending them to the viewer app, and extracting design data, and Viewer for rendering 2D and 3D models.

Maintained by Paul Govan. Last updated 6 months ago.

3d-models autodesk viewer

5.8 match 7 stars 6.13 score 16 scripts

biodiverse

unmarked:Models for Data from Unmarked Animals

Fits hierarchical models of animal abundance and occurrence to data collected using survey methods such as point counts, site occupancy sampling, distance sampling, removal sampling, and double observer sampling. Parameters governing the state and observation processes can be modeled as functions of covariates. References: Kellner et al. (2023) <doi:10.1111/2041-210X.14123>, Fiske and Chandler (2011) <doi:10.18637/jss.v043.i10>.

Maintained by Ken Kellner. Last updated 1 days ago.

openblas cpp openmp

2.7 match 4 stars 13.03 score 652 scripts 12 dependents

bioc

singscore:Rank-based single-sample gene set scoring method

A simple single-sample gene signature scoring method that uses rank-based statistics to analyze the sample's gene expression profile. It scores the expression activities of gene sets at a single-sample level.

Maintained by Malvika Kharbanda. Last updated 5 months ago.

software geneexpression genesetenrichment bioinformatics

3.5 match 41 stars 10.03 score 124 scripts 4 dependents

jeffreyracine

crs:Categorical Regression Splines

Regression splines that handle a mix of continuous and categorical (discrete) data often encountered in applied settings. I would like to gratefully acknowledge support from the Natural Sciences and Engineering Research Council of Canada (NSERC, <https://www.nserc-crsng.gc.ca>), the Social Sciences and Humanities Research Council of Canada (SSHRC, <https://www.sshrc-crsh.gc.ca>), and the Shared Hierarchical Academic Research Computing Network (SHARCNET, <https://www.sharcnet.ca>). We would also like to acknowledge the contributions of the GNU GSL authors. In particular, we adapt the GNU GSL B-spline routine gsl_bspline.c adding automated support for quantile knots (in addition to uniform knots), providing missing functionality for derivatives, and for extending the splines beyond their endpoints.

Maintained by Jeffrey S. Racine. Last updated 3 months ago.

cpp

4.2 match 17 stars 8.30 score 90 scripts 1 dependents

mplex

multiplex:Algebraic Tools for the Analysis of Multiple Social Networks

Algebraic procedures for analyses of multiple social networks are delivered with this package as described in Ostoic (2020) <DOI:10.18637/jss.v092.i11>. 'multiplex' makes possible, among other things, to create and manipulate multiplex, multimode, and multilevel network data with different formats. Effective ways are available to treat multiple networks with routines that combine algebraic systems like the partially ordered semigroup with decomposition procedures or semiring structures with the relational bundles occurring in different types of multivariate networks. 'multiplex' provides also an algebraic approach for affiliation networks through Galois derivations between families of the pairs of subsets in the two domains of the network with visualization options.

Maintained by Antonio Rivero Ostoic. Last updated 2 months ago.

algebra network-analysis semigroup semiring

4.3 match 23 stars 8.12 score 69 scripts 2 dependents

atorus-research

metacore:A Centralized Metadata Object Focus on Clinical Trial Data Programming Workflows

Create an immutable container holding metadata for the purpose of better enabling programming activities and functionality of other packages within the clinical programming workflow.

Maintained by Christina Fillmore. Last updated 11 months ago.

4.3 match 35 stars 7.99 score 133 scripts 1 dependents

sthomas522

hmclearn:Fit Statistical Models Using Hamiltonian Monte Carlo

Provide users with a framework to learn the intricacies of the Hamiltonian Monte Carlo algorithm with hands-on experience by tuning and fitting their own models. All of the code is written in R. Theoretical references are listed below:. Neal, Radford (2011) "Handbook of Markov Chain Monte Carlo" ISBN: 978-1420079418, Betancourt, Michael (2017) "A Conceptual Introduction to Hamiltonian Monte Carlo" <arXiv:1701.02434>, Thomas, S., Tu, W. (2020) "Learning Hamiltonian Monte Carlo in R" <arXiv:2006.16194>, Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013) "Bayesian Data Analysis" ISBN: 978-1439840955, Agresti, Alan (2015) "Foundations of Linear and Generalized Linear Models ISBN: 978-1118730034, Pinheiro, J., Bates, D. (2006) "Mixed-effects Models in S and S-Plus" ISBN: 978-1441903174.

Maintained by Samuel Thomas. Last updated 4 years ago.

6.0 match 11 stars 5.64 score 16 scripts

treynkens

ReIns:Functions from "Reinsurance: Actuarial and Statistical Aspects"

Functions from the book "Reinsurance: Actuarial and Statistical Aspects" (2017) by Hansjoerg Albrecher, Jan Beirlant and Jef Teugels <https://www.wiley.com/en-us/Reinsurance%3A+Actuarial+and+Statistical+Aspects-p-9780470772683>.

Maintained by Tom Reynkens. Last updated 4 months ago.

extremes reinsurance risk-analysis cpp

5.3 match 22 stars 6.31 score 186 scripts

ysosirius

windfarmGA:Genetic Algorithm for Wind Farm Layout Optimization

The genetic algorithm is designed to optimize wind farms of any shape. It requires a predefined amount of turbines, a unified rotor radius and an average wind speed value for each incoming wind direction. A terrain effect model can be included that downloads an 'SRTM' elevation model and loads a Corine Land Cover raster to approximate surface roughness.

Maintained by Sebastian Gatscha. Last updated 2 months ago.

windfarm-layout optimization genetic-algorithm renewable-energy cpp

6.7 match 27 stars 5.06 score 17 scripts

glenndavis52

spacesXYZ:CIE XYZ and some of Its Derived Color Spaces

Functions for converting among CIE XYZ, xyY, Lab, and Luv. Calculate Correlated Color Temperature (CCT) and the Planckian and daylight loci. The XYZs of some standard illuminants and some standard linear chromatic adaptation transforms (CATs) are included. Three standard color difference metrics are included, plus the forward direction of the 'CIECAM02' color appearance model.

Maintained by Glenn Davis. Last updated 1 months ago.

4.8 match 7.03 score 21 scripts 32 dependents

otoomet

maxLik:Maximum Likelihood Estimation and Related Tools

Functions for Maximum Likelihood (ML) estimation, non-linear optimization, and related tools. It includes a unified way to call different optimizers, and classes and methods to handle the results from the Maximum Likelihood viewpoint. It also includes a number of convenience tools for testing and developing your own models.

Maintained by Ott Toomet. Last updated 12 months ago.

3.7 match 9.08 score 480 scripts 109 dependents

mattmar

rasterdiv:Diversity Indices for Numerical Matrices

Provides methods to calculate diversity indices on numerical matrices based on information theory, as described in Rocchini, Marcantonio and Ricotta (2017) <doi:10.1016/j.ecolind.2016.07.039>, and Rocchini et al. (2021) <doi:10.1101/2021.01.23.427872>.

Maintained by Matteo Marcantonio. Last updated 20 days ago.

4.2 match 15 stars 7.65 score 44 scripts 1 dependents

qsbase

qs:Quick Serialization of R Objects

Provides functions for quickly writing and reading any R object to and from disk.

Maintained by Travers Ching. Last updated 10 days ago.

compression data-storage encoding serialization libzstd lz4 cpp

2.3 match 414 stars 13.91 score 2.5k scripts 51 dependents

jeffreyracine

np:Nonparametric Kernel Smoothing Methods for Mixed Data Types

Nonparametric (and semiparametric) kernel methods that seamlessly handle a mix of continuous, unordered, and ordered factor data types. We would like to gratefully acknowledge support from the Natural Sciences and Engineering Research Council of Canada (NSERC, <https://www.nserc-crsng.gc.ca/>), the Social Sciences and Humanities Research Council of Canada (SSHRC, <https://www.sshrc-crsh.gc.ca/>), and the Shared Hierarchical Academic Research Computing Network (SHARCNET, <https://sharcnet.ca/>). We would also like to acknowledge the contributions of the GNU GSL authors. In particular, we adapt the GNU GSL B-spline routine gsl_bspline.c adding automated support for quantile knots (in addition to uniform knots), providing missing functionality for derivatives, and for extending the splines beyond their endpoints.

Maintained by Jeffrey S. Racine. Last updated 1 months ago.

2.5 match 49 stars 12.64 score 672 scripts 44 dependents

bioc

DuplexDiscovereR:Analysis of the data from RNA duplex probing experiments

DuplexDiscovereR is a package designed for analyzing data from RNA cross-linking and proximity ligation protocols such as SPLASH, PARIS, LIGR-seq, and others. DuplexDiscovereR accepts input in the form of chimerically or split-aligned reads. It includes procedures for alignment classification, filtering, and efficient clustering of individual chimeric reads into duplex groups (DGs). Once DGs are identified, the package predicts RNA duplex formation and their hybridization energies. Additional metrics, such as p-values for random ligation hypothesis or mean DG alignment scores, can be calculated to rank final set of RNA duplexes. Data from multiple experiments or replicates can be processed separately and further compared to check the reproducibility of the experimental method.

Maintained by Egor Semenchenko. Last updated 2 months ago.

sequencing transcriptomics structuralprediction clustering splicedalignment

6.9 match 1 stars 4.60 score 5 scripts

cran

ragtop:Pricing Equity Derivatives with Extensions of Black-Scholes

Algorithms to price American and European equity options, convertible bonds and a variety of other financial derivatives. It uses an extension of the usual Black-Scholes model in which jump to default may occur at a probability specified by a power-law link between stock price and hazard rate as found in the paper by Takahashi, Kobayashi, and Nakagawa (2001) <doi:10.3905/jfi.2001.319302>. We use ideas and techniques from Andersen and Buffum (2002) <doi:10.2139/ssrn.355308> and Linetsky (2006) <doi:10.1111/j.1467-9965.2006.00271.x>.

Maintained by Brian K. Boonstra. Last updated 5 years ago.

11.6 match 2.70 score

shaunpwilkinson

aphid:Analysis with Profile Hidden Markov Models

Designed for the development and application of hidden Markov models and profile HMMs for biological sequence analysis. Contains functions for multiple and pairwise sequence alignment, model construction and parameter optimization, file import/export, implementation of the forward, backward and Viterbi algorithms for conditional sequence probabilities, tree-based sequence weighting, and sequence simulation. Features a wide variety of potential applications including database searching, gene-finding and annotation, phylogenetic analysis and sequence classification. Based on the models and algorithms described in Durbin et al (1998, ISBN: 9780521629713).

Maintained by Shaun Wilkinson. Last updated 8 months ago.

cpp

4.7 match 22 stars 6.58 score 38 scripts 3 dependents

merck

gsDesign2:Group Sequential Design with Non-Constant Effect

The goal of 'gsDesign2' is to enable fixed or group sequential design under non-proportional hazards. To enable highly flexible enrollment, time-to-event and time-to-dropout assumptions, 'gsDesign2' offers piecewise constant enrollment, failure rates, and dropout rates for a stratified population. This package includes three methods for designs: average hazard ratio, weighted logrank tests in Yung and Liu (2019) <doi:10.1111/biom.13196>, and MaxCombo tests. Substantial flexibility on top of what is in the 'gsDesign' package is intended for selecting boundaries.

Maintained by Yujie Zhao. Last updated 3 days ago.

cpp

3.5 match 22 stars 8.91 score 186 scripts

joeguinness

GpGp:Fast Gaussian Process Computation Using Vecchia's Approximation

Functions for fitting and doing predictions with Gaussian process models using Vecchia's (1988) approximation. Package also includes functions for reordering input locations, finding ordered nearest neighbors (with help from 'FNN' package), grouping operations, and conditional simulations. Covariance functions for spatial and spatial-temporal data on Euclidean domains and spheres are provided. The original approximation is due to Vecchia (1988) <http://www.jstor.org/stable/2345768>, and the reordering and grouping methods are from Guinness (2018) <doi:10.1080/00401706.2018.1437476>. Model fitting employs a Fisher scoring algorithm described in Guinness (2019) <doi:10.48550/arXiv.1905.08374>.

Maintained by Joseph Guinness. Last updated 5 months ago.

openblas cpp openmp

5.0 match 10 stars 6.16 score 160 scripts 6 dependents

mclements

etm:Empirical Transition Matrix

The etm (empirical transition matrix) package permits to estimate the matrix of transition probabilities for any time-inhomogeneous multi-state model with finite state space using the Aalen-Johansen estimator. Functions for data preparation and for displaying are also included (Allignol et al., 2011 <doi:10.18637/jss.v038.i04>). Functionals of the Aalen-Johansen estimator, e.g., excess length-of-stay in an intermediate state, can also be computed (Allignol et al. 2011 <doi:10.1007/s00180-010-0200-x>).

Maintained by Arthur Allignol. Last updated 3 years ago.

openblas cpp

3.8 match 8.09 score 110 scripts 13 dependents

carlos-alberto-silva

rGEDI:NASA's Global Ecosystem Dynamics Investigation (GEDI) Data Visualization and Processing

Set of tools for downloading, reading, visualizing and processing GEDI Level1B, Level2A and Level2B data.

Maintained by Caio Hamamura. Last updated 5 months ago.

4.9 match 169 stars 6.11 score 85 scripts 1 dependents

bioc

rawrr:Direct Access to Orbitrap Data and Beyond

This package wraps the functionality of the Thermo Fisher Scientic RawFileReader .NET 8.0 assembly. Within the R environment, spectra and chromatograms are represented by S3 objects. The package provides basic functions to download and install the required third-party libraries. The package is developed, tested, and used at the Functional Genomics Center Zurich, Switzerland.

Maintained by Christian Panse. Last updated 3 months ago.

massspectrometry proteomics metabolomics infrastructure software fast mass-spectrometry multiplatform orbitrap-ms

3.7 match 56 stars 8.19 score 23 scripts 2 dependents

carlos-alberto-silva

ForestGapR:Tropical Forest Canopy Gaps Analysis

Set of tools for detecting and analyzing Airborne Laser Scanning-derived Tropical Forest Canopy Gaps. Details were published in Silva and others (2019) <doi:10.1111/2041-210X.13211>.

Maintained by Carlos Alberto Silva. Last updated 1 years ago.

5.7 match 30 stars 5.26 score 24 scripts

bsaul

inferference:Methods for Causal Inference with Interference

Provides methods for estimating causal effects in the presence of interference described in B. Saul and M. Hugdens (2017) <doi:10.18637/jss.v082.i02>. Currently it implements the inverse-probability weighted (IPW) estimators proposed by E.J. Tchetgen Tchetgen and T.J. Vanderweele (2012) <doi:10.1177/0962280210386779>.

Maintained by Bradley Saul. Last updated 4 years ago.

5.5 match 6 stars 5.47 score 49 scripts

cran

interp:Interpolation Methods

Bivariate data interpolation on regular and irregular grids, either linear or using splines are the main part of this package. It is intended to provide FOSS replacement functions for the ACM licensed akima::interp and tripack::tri.mesh functions. Linear interpolation is implemented in interp::interp(..., method="linear"), this corresponds to the call akima::interp(..., linear=TRUE) which is the default setting and covers most of akima::interp use cases in depending packages. A re-implementation of Akimas irregular grid spline interpolation (akima::interp(..., linear=FALSE)) is now also available via interp::interp(..., method="akima"). Estimators for partial derivatives are now also available in interp::locpoly(), these are a prerequisite for the spline interpolation. The basic part is a GPLed triangulation algorithm (sweep hull algorithm by David Sinclair) providing the starting point for the irregular grid interpolator. As side effect this algorithm is also used to provide replacements for almost all functions of the tripack package which also suffers from the same ACM license restrictions. All functions are designed to be backward compatible with their akima / tripack counterparts.

Maintained by Albrecht Gebhardt. Last updated 1 years ago.

fortran cpp

3.3 match 1 stars 9.06 score 228 scripts 286 dependents

sritchie73

ukbnmr:Removal of Unwanted Technical Variation from UK Biobank NMR Metabolomics Biomarker Data

A suite of utilities for working with the UK Biobank <https://www.ukbiobank.ac.uk/> Nuclear Magnetic Resonance spectroscopy (NMR) metabolomics data <https://biobank.ndph.ox.ac.uk/showcase/label.cgi?id=220>. Includes functions for extracting biomarkers from decoded UK Biobank field data, removing unwanted technical variation from biomarker concentrations, computing an extended set of lipid, fatty acid, and cholesterol fractions, and for re-deriving composite biomarkers and ratios after adjusting data for unwanted biological variation. For further details on methods see Ritchie SC et al. Sci Data (2023) <doi:10.1038/s41597-023-01949-y>.

Maintained by Scott C Ritchie. Last updated 4 months ago.

5.0 match 33 stars 5.82 score 6 scripts

cran

scam:Shape Constrained Additive Models

Generalized additive models under shape constraints on the component functions of the linear predictor. Models can include multiple shape-constrained (univariate and bivariate) and unconstrained terms. Routines of the package 'mgcv' are used to set up the model matrix, print, and plot the results. Multiple smoothing parameter estimation by the Generalized Cross Validation or similar. See Pya and Wood (2015) <doi:10.1007/s11222-013-9448-7> for an overview. A broad selection of shape-constrained smoothers, linear functionals of smooths with shape constraints, and Gaussian models with AR1 residuals.

Maintained by Natalya Pya. Last updated 2 months ago.

4.0 match 5 stars 7.17 score 388 scripts 23 dependents

gmgeorg

LambertW:Probabilistic Models to Analyze and Gaussianize Heavy-Tailed, Skewed Data

Lambert W x F distributions are a generalized framework to analyze skewed, heavy-tailed data. It is based on an input/output system, where the output random variable (RV) Y is a non-linearly transformed version of an input RV X ~ F with similar properties as X, but slightly skewed (heavy-tailed). The transformed RV Y has a Lambert W x F distribution. This package contains functions to model and analyze skewed, heavy-tailed data the Lambert Way: simulate random samples, estimate parameters, compute quantiles, and plot/ print results nicely. The most useful function is 'Gaussianize', which works similarly to 'scale', but actually makes the data Gaussian. A do-it-yourself toolkit allows users to define their own Lambert W x 'MyFavoriteDistribution' and use it in their analysis right away.

Maintained by Georg M. Goerg. Last updated 1 years ago.

gaussianize gaussianize-data heavy-tailed heavy-tailed-distributions leptokurtosis normal-distribution normalization skewed-data statistics cpp

3.5 match 10 stars 8.17 score 78 scripts 13 dependents

cran

datarobot:'DataRobot' Predictive Modeling API

For working with the 'DataRobot' predictive modeling platform's API <https://www.datarobot.com/>.

Maintained by AJ Alon. Last updated 1 years ago.

8.3 match 2 stars 3.48 score

rvlenth

emmeans:Estimated Marginal Means, aka Least-Squares Means

Obtain estimated marginal means (EMMs) for many linear, generalized linear, and mixed models. Compute contrasts or linear functions of EMMs, trends, and comparisons of slopes. Plots and other displays. Least-squares means are discussed, and the term "estimated marginal means" is suggested, in Searle, Speed, and Milliken (1980) Population marginal means in the linear model: An alternative to least squares means, The American Statistician 34(4), 216-221 <doi:10.1080/00031305.1980.10483031>.

Maintained by Russell V. Lenth. Last updated 3 days ago.

1.5 match 377 stars 19.19 score 13k scripts 187 dependents

cran

Select:Determines Species Probabilities Based on Functional Traits

The objective of these functions is to derive a species assemblage that satisfies a functional trait profile. Restoring resilient ecosystems requires a flexible framework for selecting assemblages that are based on the functional traits of species. However, current trait-based models have been limited to algorithms that can only select species by optimising specific trait values, and could not elegantly accommodate the common desire among restoration ecologists to produce functionally diverse assemblages. We have solved this problem by applying a non-linear optimisation algorithm that optimises Rao Q, a closed-form functional trait diversity index that incorporates species abundances, subject to other linear constraints. This framework generalises previous models that only optimised the entropy of the community, and can optimise both functional diversity and entropy simultaneously. This package can also be used to generate experimental assemblages to test the effects of community-level traits on community dynamics and ecosystem function. The method is based on theory discussed in Laughlin (2014, Ecology Letters) <doi.org/10.1111/ele.12288>.

Maintained by Daniel Laughlin. Last updated 7 years ago.

8.3 match 3.45 score 28 scripts

symengine

symengine:Interface to the 'SymEngine' Library

Provides an R interface to 'SymEngine' <https://github.com/symengine/>, a standalone 'C++' library for fast symbolic manipulation. The package has functionalities for symbolic computation like calculating exact mathematical expressions, solving systems of linear equations and code generation.

Maintained by Jialin Ma. Last updated 1 years ago.

mpfr4 gmp cpp

3.5 match 26 stars 8.20 score 33 scripts 10 dependents

psychmeta

psychmeta:Psychometric Meta-Analysis Toolkit

Tools for computing bare-bones and psychometric meta-analyses and for generating psychometric data for use in meta-analysis simulations. Supports bare-bones, individual-correction, and artifact-distribution methods for meta-analyzing correlations and d values. Includes tools for converting effect sizes, computing sporadic artifact corrections, reshaping meta-analytic databases, computing multivariate corrections for range variation, and more. Bugs can be reported to <https://github.com/psychmeta/psychmeta/issues> or <issues@psychmeta.com>.

Maintained by Jeffrey A. Dahlke. Last updated 9 months ago.

hacktoberfest meta-analysis psychology psychometric psychometrics

3.5 match 57 stars 8.25 score 151 scripts

ctn-0094

public.ctn0094extra:Helper Files for the CTN-0094 Relational Database

Engineered features and "helper" functions ancillary to the 'public.ctn0094data' package, extending this package for ease of use (see <https://CRAN.R-project.org/package=public.ctn0094data>). This 'public.ctn0094data' package contains harmonized datasets from some of the National Institute of Drug Abuse's Clinical Trials Network (NIDA's CTN) projects. Specifically, the CTN-0094 project is to harmonize and de-identify clinical trials data from the CTN-0027, CTN-0030, and CTN-51 studies for opioid use disorder. This current version is built from 'public.ctn0094data' v. 1.0.6.

Maintained by Gabriel Odom. Last updated 1 years ago.

7.3 match 3.88 score 15 scripts

daijiang

rtrees:Deriving Phylogenies from Synthesis Trees

To facilitate generating phylogenies from synthesis trees.

Maintained by Daijiang Li. Last updated 9 months ago.

phylogenetic-trees

5.0 match 33 stars 5.68 score 73 scripts

fauvernierma

survPen:Multidimensional Penalized Splines for (Excess) Hazard Models, Relative Mortality Ratio Models and Marginal Intensity Models

Fits (excess) hazard, relative mortality ratio or marginal intensity models with multidimensional penalized splines allowing for time-dependent effects, non-linear effects and interactions between several continuous covariates. In survival and net survival analysis, in addition to modelling the effect of time (via the baseline hazard), one has often to deal with several continuous covariates and model their functional forms, their time-dependent effects, and their interactions. Model specification becomes therefore a complex problem and penalized regression splines represent an appealing solution to that problem as splines offer the required flexibility while penalization limits overfitting issues. Current implementations of penalized survival models can be slow or unstable and sometimes lack some key features like taking into account expected mortality to provide net survival and excess hazard estimates. In contrast, survPen provides an automated, fast, and stable implementation (thanks to explicit calculation of the derivatives of the likelihood) and offers a unified framework for multidimensional penalized hazard and excess hazard models. Later versions (>2.0.0) include penalized models for relative mortality ratio, and marginal intensity in recurrent event setting. survPen may be of interest to those who 1) analyse any kind of time-to-event data: mortality, disease relapse, machinery breakdown, unemployment, etc 2) wish to describe the associated hazard and to understand which predictors impact its dynamics, 3) wish to model the relative mortality ratio between a cohort and a reference population, 4) wish to describe the marginal intensity for recurrent event data. See Fauvernier et al. (2019a) <doi:10.21105/joss.01434> for an overview of the package and Fauvernier et al. (2019b) <doi:10.1111/rssc.12368> for the method.

Maintained by Mathieu Fauvernier. Last updated 4 months ago.

cpp

4.1 match 12 stars 6.82 score 85 scripts 1 dependents

jlaake

RMark:R Code for Mark Analysis

An interface to the software package MARK that constructs input files for MARK and extracts the output. MARK was developed by Gary White and is freely available at <http://www.phidot.org/software/mark/downloads/> but is not open source.

Maintained by Jeff Laake. Last updated 3 years ago.

5.8 match 4.90 score 366 scripts 4 dependents

bucky2177

dRiftDM:Estimating (Time-Dependent) Drift Diffusion Models

Fit and explore Drift Diffusion Models (DDMs), a common tool in psychology for describing decision processes in simple tasks. It can handle both time-independent and time-dependent DDMs. You either choose prebuilt models or create your own, and the package takes care of model predictions and parameter estimation. Model predictions are derived via the numerical solutions provided by Richter, Ulrich, and Janczyk (2023, <doi:10.1016/j.jmp.2023.102756>).

Maintained by Valentin Koob. Last updated 13 days ago.

cpp

4.3 match 6 stars 6.58 score 5 scripts

nathanieltwarog

braidrm:Fitting Combined Action with the BRAID Response Surface Model

Contains functions for evaluating, analyzing, and fitting combined action dose response surfaces with the Bivariate Response to Additive Interacting Doses (BRAID) model of combined action, along with tools for implementing other combination analysis methods, including Bliss independence, combination index, and additional response surface methods.

Maintained by Nathaniel R. Twarog. Last updated 6 months ago.

4.6 match 1 stars 6.10 score 35 scripts 1 dependents

robinhankin

weyl:The Weyl Algebra

A suite of routines for Weyl algebras. Notation follows Coutinho (1995, ISBN 0-521-55119-6, "A Primer of Algebraic D-Modules"). Uses 'disordR' discipline (Hankin 2022 <doi:10.48550/arXiv.2210.03856>). To cite the package in publications, use Hankin 2022 <doi:10.48550/arXiv.2212.09230>.

Maintained by Robin K. S. Hankin. Last updated 2 months ago.

5.0 match 3 stars 5.59 score 4 scripts

dschulz13

smoots:Nonparametric Estimation of the Trend and Its Derivatives in TS

The nonparametric trend and its derivatives in equidistant time series (TS) with short-memory stationary errors can be estimated. The estimation is conducted via local polynomial regression using an automatically selected bandwidth obtained by a built-in iterative plug-in algorithm or a bandwidth fixed by the user. A Nadaraya-Watson kernel smoother is also built-in as a comparison. With version 1.1.0, a linearity test for the trend function, forecasting methods and backtesting approaches are implemented as well. The smoothing methods of the package are described in Feng, Y., Gries, T., and Fritz, M. (2020) <doi:10.1080/10485252.2020.1759598>.

Maintained by Dominik Schulz. Last updated 2 years ago.

openblas cpp openmp

10.5 match 2.65 score 6 scripts 3 dependents

andy-iskauskas

hmer:History Matching and Emulation Package

A set of objects and functions for Bayes Linear emulation and history matching. Core functionality includes automated training of emulators to data, diagnostic functions to ensure suitability, and a variety of proposal methods for generating 'waves' of points. For details on the mathematical background, there are many papers available on the topic (see references attached to function help files or the below references); for details of the functions in this package, consult the manual or help files. Iskauskas, A, et al. (2024) <doi:10.18637/jss.v109.i10>. Bower, R.G., Goldstein, M., and Vernon, I. (2010) <doi:10.1214/10-BA524>. Craig, P.S., Goldstein, M., Seheult, A.H., and Smith, J.A. (1997) <doi:10.1007/978-1-4612-2290-3_2>.

Maintained by Andrew Iskauskas. Last updated 12 days ago.

3.9 match 16 stars 7.19 score 37 scripts

bioc

tidySummarizedExperiment:Brings SummarizedExperiment to the Tidyverse

The tidySummarizedExperiment package provides a set of tools for creating and manipulating tidy data representations of SummarizedExperiment objects. SummarizedExperiment is a widely used data structure in bioinformatics for storing high-throughput genomic data, such as gene expression or DNA sequencing data. The tidySummarizedExperiment package introduces a tidy framework for working with SummarizedExperiment objects. It allows users to convert their data into a tidy format, where each observation is a row and each variable is a column. This tidy representation simplifies data manipulation, integration with other tidyverse packages, and enables seamless integration with the broader ecosystem of tidy tools for data analysis.

Maintained by Stefano Mangiola. Last updated 5 months ago.

assaydomain infrastructure rnaseq differentialexpression geneexpression normalization clustering qualitycontrol sequencing transcription transcriptomics

3.3 match 26 stars 8.44 score 196 scripts 1 dependents

cran

KneeArrower:Finds Cutoff Points on Knee Curves

Given a set of points around a knee curve, analyzes first and second derivatives to find knee points.

Maintained by Alan Tseng. Last updated 4 years ago.

8.5 match 3.18 score 1 dependents

xitingwang-ida

sysAgNPs:Systematic Quantification of AgNPs to Unleash their Potential for Applicability

There is variation across AgNPs due to differences in characterization techniques and testing metrics employed in studies. To address this problem, we have developed a systematic evaluation framework called 'sysAgNPs'. Within this framework, Distribution Entropy (DE) is utilized to measure the uncertainty of feature categories of AgNPs, Proclivity Entropy (PE) assesses the preference of these categories, and Combination Entropy (CE) quantifies the uncertainty of feature combinations of AgNPs. Additionally, a Markov chain model is employed to examine the relationships among the sub-features of AgNPs and to determine a Transition Score (TS) scoring standard that is based on steady-state probabilities. The 'sysAgNPs' framework provides metrics for evaluating AgNPs, which helps to unravel their complexity and facilitates effective comparisons among different AgNPs, thereby advancing the scientific research and application of these AgNPs.

Maintained by Xiting Wang. Last updated 15 days ago.

7.9 match 3.40 score

ddediu

AdhereR:Adherence to Medications

Computation of adherence to medications from Electronic Health care Data and visualization of individual medication histories and adherence patterns. The package implements a set of S3 classes and functions consistent with current adherence guidelines and definitions. It allows the computation of different measures of adherence (as defined in the literature, but also several original ones), their publication-quality plotting, the estimation of event duration and time to initiation, the interactive exploration of patient medication history and the real-time estimation of adherence given various parameter settings. It scales from very small datasets stored in flat CSV files to very large databases and from single-thread processing on mid-range consumer laptops to parallel processing on large heterogeneous computing clusters. It exposes a standardized interface allowing it to be used from other programming languages and platforms, such as Python.

Maintained by Dan Dediu. Last updated 1 years ago.

adherence-to-medications electronic-healthcare-data hadoop medical-databases medication-histories python sql visualisation

3.8 match 28 stars 7.07 score 47 scripts 1 dependents

cran

circular:Circular Statistics

Circular Statistics, from "Topics in circular Statistics" (2001) S. Rao Jammalamadaka and A. SenGupta, World Scientific.

Maintained by Eduardo García-Portugués. Last updated 7 months ago.

fortran

3.4 match 7 stars 7.76 score 1.1k scripts 40 dependents

nandp1

nser:Bhavcopy and Live Market Data from National Stock Exchange (NSE) & Bombay Stock Exchange (BSE) India

Download Current & Historical Bhavcopy. Get Live Market data from NSE India of Equities and Derivatives (F&O) segment. Data source <https://www.nseindia.com/>.

Maintained by Nandan Patil. Last updated 4 months ago.

bhav bhavcopy bhavcopy-downloader financial-data market-data national-stock-exchange nse nse-stock-data option-pricing optionchain rselenium stock-prices

3.4 match 8 stars 7.61 score 76 scripts

bioc

MultiAssayExperiment:Software for the integration of multi-omics experiments in Bioconductor

Harmonize data management of multiple experimental assays performed on an overlapping set of specimens. It provides a familiar Bioconductor user experience by extending concepts from SummarizedExperiment, supporting an open-ended mix of standard data classes for individual assays, and allowing subsetting by genomic ranges or rownames. Facilities are provided for reshaping data into wide and long formats for adaptability to graphing and downstream analysis.

Maintained by Marcel Ramos. Last updated 2 months ago.

infrastructure datarepresentation bioconductor bioconductor-package genomics nci-itcr tcga u24ca289073

1.8 match 71 stars 14.95 score 670 scripts 127 dependents

r-lidar

lidR:Airborne LiDAR Data Manipulation and Visualization for Forestry Applications

Airborne LiDAR (Light Detection and Ranging) interface for data manipulation and visualization. Read/write 'las' and 'laz' files, computation of metrics in area based approach, point filtering, artificial point reduction, classification from geographic data, normalization, individual tree segmentation and other manipulations.

Maintained by Jean-Romain Roussel. Last updated 1 months ago.

als forestry las laz lidar point-cloud remote-sensing openblas cpp openmp

1.8 match 623 stars 14.47 score 844 scripts 8 dependents

lme4

lme4:Linear Mixed-Effects Models using 'Eigen' and S4

Fit linear and generalized linear mixed-effects models. The models and their components are represented using S4 classes and methods. The core computational algorithms are implemented using the 'Eigen' C++ library for numerical linear algebra and 'RcppEigen' "glue".

Maintained by Ben Bolker. Last updated 3 days ago.

cpp

1.3 match 647 stars 20.69 score 35k scripts 1.5k dependents

epiforesite

facilityepimath:Analyze Mathematical Models of Healthcare Facility Transmission

Calculate useful quantities for a user-defined differential equation model of infectious disease transmission among individuals in a healthcare facility. Input rates of transition between states of individuals with and without the disease-causing organism, distributions of states at facility admission, relative infectivity of transmissible states, and the facility length of stay distribution. Calculate the model equilibrium and the basic facility reproduction number, as described in Toth et al. (2025) <doi:10.1101/2025.02.21.25322698>.

Maintained by Damon Toth. Last updated 5 days ago.

5.0 match 5.18 score

bioc

xcms:LC-MS and GC-MS Data Analysis

Framework for processing and visualization of chromatographically separated and single-spectra mass spectral data. Imports from AIA/ANDI NetCDF, mzXML, mzData and mzML files. Preprocesses data for high-throughput, untargeted analyte profiling.

Maintained by Steffen Neumann. Last updated 3 days ago.

immunooncology massspectrometry metabolomics bioconductor feature-detection mass-spectrometry peak-detection cpp

1.8 match 196 stars 14.31 score 984 scripts 11 dependents

kbroman

qtl:Tools for Analyzing QTL Experiments

Analysis of experimental crosses to identify genes (called quantitative trait loci, QTLs) contributing to variation in quantitative traits. Broman et al. (2003) <doi:10.1093/bioinformatics/btg112>.

Maintained by Karl W Broman. Last updated 7 months ago.

openblas

2.0 match 80 stars 12.79 score 2.4k scripts 29 dependents

winvector

cdata:Fluid Data Transformations

Supplies higher-order coordinatized data specification and fluid transform operators that include pivot and anti-pivot as special cases. The methodology is describe in 'Zumel', 2018, "Fluid data reshaping with 'cdata'", <https://winvector.github.io/FluidData/FluidDataReshapingWithCdata.html> , <DOI:10.5281/zenodo.1173299> . This package introduces the idea of explicit control table specification of data transforms. Works on in-memory data or on remote data using 'rquery' and 'SQL' database interfaces.

Maintained by John Mount. Last updated 6 months ago.

3.3 match 46 stars 7.82 score 71 scripts 1 dependents

dnychka

fields:Tools for Spatial Data

For curve, surface and function fitting with an emphasis on splines, spatial data, geostatistics, and spatial statistics. The major methods include cubic, and thin plate splines, Kriging, and compactly supported covariance functions for large data sets. The splines and Kriging methods are supported by functions that can determine the smoothing parameter (nugget and sill variance) and other covariance function parameters by cross validation and also by restricted maximum likelihood. For Kriging there is an easy to use function that also estimates the correlation scale (range parameter). A major feature is that any covariance function implemented in R and following a simple format can be used for spatial prediction. There are also many useful functions for plotting and working with spatial data as images. This package also contains an implementation of sparse matrix methods for large spatial data sets and currently requires the sparse matrix (spam) package. Use help(fields) to get started and for an overview. The fields source code is deliberately commented and provides useful explanations of numerical details as a companion to the manual pages. The commented source code can be viewed by expanding the source code version and looking in the R subdirectory. The reference for fields can be generated by the citation function in R and has DOI <doi:10.5065/D6W957CT>. Development of this package was supported in part by the National Science Foundation Grant 1417857, the National Center for Atmospheric Research, and Colorado School of Mines. See the Fields URL for a vignette on using this package and some background on spatial statistics.

Maintained by Douglas Nychka. Last updated 9 months ago.

fortran

2.0 match 15 stars 12.60 score 7.7k scripts 295 dependents

abarbour

psd:Adaptive, Sine-Multitaper Power Spectral Density and Cross Spectrum Estimation

Produces power spectral density estimates through iterative refinement of the optimal number of sine-tapers at each frequency. This optimization procedure is based on the method of Riedel and Sidorenko (1995), which minimizes the Mean Square Error (sum of variance and bias) at each frequency, but modified for computational stability. The same procedure can now be used to calculate the cross spectrum (multivariate analyses).

Maintained by Andrew J. Barbour. Last updated 2 years ago.

multitaper power-spectral-density power-spectrum psd spectral-density-estimates spectrum openblas cpp

3.5 match 9 stars 7.12 score 122 scripts 1 dependents

bioc

phyloseq:Handling and analysis of high-throughput microbiome census data

phyloseq provides a set of classes and tools to facilitate the import, storage, analysis, and graphical display of microbiome census data.

Maintained by Paul J. McMurdie. Last updated 5 months ago.

immunooncology sequencing microbiome metagenomics clustering classification multiplecomparison geneticvariability

1.8 match 597 stars 13.90 score 8.4k scripts 37 dependents

tidyfun

tf:S3 Classes and Methods for Tidy Functional Data

Defines S3 vector data types for vectors of functional data (grid-based, spline-based or functional principal components-based) with all arithmetic and summary methods, derivation, integration and smoothing, plotting, data import and export, and data wrangling, such as re-evaluating, subsetting, sub-assigning, zooming into sub-domains, or extracting functional features like minima/maxima and their locations. The implementation allows including such vectors in data frames for joint analysis of functional and scalar variables.

Maintained by Fabian Scheipl. Last updated 4 days ago.

4.1 match 7 stars 6.14 score 13 scripts 2 dependents

vincentarelbundock

marginaleffects:Predictions, Comparisons, Slopes, Marginal Means, and Hypothesis Tests

Compute and plot predictions, slopes, marginal means, and comparisons (contrasts, risk ratios, odds, etc.) for over 100 classes of statistical and machine learning models in R. Conduct linear and non-linear hypothesis tests, or equivalence tests. Calculate uncertainty estimates using the delta method, bootstrapping, or simulation-based inference. Details can be found in Arel-Bundock, Greifer, and Heiss (2024) <doi:10.18637/jss.v111.i09>.

Maintained by Vincent Arel-Bundock. Last updated 11 hours ago.

cpp

1.7 match 505 stars 14.51 score 1.8k scripts 9 dependents

ropensci

rgbif:Interface to the Global Biodiversity Information Facility API

A programmatic interface to the Web Service methods provided by the Global Biodiversity Information Facility (GBIF; <https://www.gbif.org/developer/summary>). GBIF is a database of species occurrence records from sources all over the globe. rgbif includes functions for searching for taxonomic names, retrieving information on data providers, getting species occurrence records, getting counts of occurrence records, and using the GBIF tile map service to make rasters summarizing huge amounts of data.

Maintained by John Waller. Last updated 3 days ago.

gbif specimens api web-services occurrences species taxonomy biodiversity data lifewatch oscibio spocc

1.9 match 161 stars 13.26 score 2.1k scripts 20 dependents

bobjansen

scrypt:Key Derivation Functions for R Based on Scrypt

Functions for working with the scrypt key derivation functions originally described by Colin Percival <https://www.tarsnap.com/scrypt/scrypt.pdf> and in Percival and Josefsson (2016) <doi:10.17487/RFC7914>. Scrypt is a password-based key derivation function created by Colin Percival. The algorithm was specifically designed to make it costly to perform large-scale custom hardware attacks by requiring large amounts of memory.

Maintained by Bob Jansen. Last updated 2 years ago.

cpp

5.5 match 4.48 score 5 scripts 5 dependents

dfsp-spirit

fsbrain:Managing and Visualizing Brain Surface Data

Provides high-level access to neuroimaging data from standard software packages like 'FreeSurfer' <http://freesurfer.net/> on the level of subjects and groups. Load morphometry data, surfaces and brain parcellations based on atlases. Mask data using labels, load data for specific atlas regions only, and visualize data and statistical results directly in 'R'.

Maintained by Tim Schäfer. Last updated 4 months ago.

3d brain dti freesurfer mesh mri neuroimaging research surface visualization voxel

3.8 match 66 stars 6.47 score 15 scripts

plambertuliege

cubicBsplines:Computation of a Cubic B-Spline Basis and Its Derivatives

Computation of a cubic B-spline basis for arbitrary knots. It also provides the 1st and 2nd derivatives, as well as the integral of the basis elements. It is used by the author to fit penalized B-spline models, see e.g. Jullion, A. and Lambert, P. (2006) <doi:10.1016/j.csda.2006.09.027>, Lambert, P. and Eilers, P.H.C. (2009) <doi:10.1016/j.csda.2008.11.022> and, more recently, Lambert, P. (2021) <doi:10.1016/j.csda.2021.107250>. It is inspired by the algorithm developed by de Boor, C. (1977) <doi:10.1137/0714026>.

Maintained by Philippe Lambert. Last updated 2 years ago.

fortran

6.7 match 1 stars 3.65 score 2 scripts 3 dependents

edsandorf

spdesign:Designing Stated Preference Experiments

Contemporary software commonly used to design stated preference experiments are expensive and the code is closed source. This is a free software package with an easy to use interface to make flexible stated preference experimental designs using state-of-the-art methods. For an overview of stated choice experimental design theory, see e.g., Rose, J. M. & Bliemer, M. C. J. (2014) in Hess S. & Daly. A. <doi:10.4337/9781781003152>. The package website can be accessed at <https://spdesign.edsandorf.me>. We acknowledge funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant INSPiRE (Grant agreement ID: 793163).

Maintained by Erlend Dancke Sandorf. Last updated 5 months ago.

5.3 match 4.60 score 20 scripts

dtharvey

titrationCurves:Acid/Base, Complexation, Redox, and Precipitation Titration Curves

A collection of functions to plot acid/base titration curves (pH vs. volume of titrant), complexation titration curves (pMetal vs. volume of EDTA), redox titration curves (potential vs.volume of titrant), and precipitation titration curves (either pAnalyte or pTitrant vs. volume of titrant). Options include the titration of mixtures, the ability to overlay two or more titration curves, and the ability to show equivalence points.

Maintained by David Harvey. Last updated 5 years ago.

5.0 match 6 stars 4.86 score 24 scripts

bioc

TSAR:Thermal Shift Analysis in R

This package automates analysis workflow for Thermal Shift Analysis (TSA) data. Processing, analyzing, and visualizing data through both shiny applications and command lines. Package aims to simplify data analysis and offer front to end workflow, from raw data to multiple trial analysis.

Maintained by Xinlin Gao. Last updated 5 months ago.

software shinyapps visualization qpcr

5.0 match 4.78 score 8 scripts

philipmostert

PointedSDMs:Fit Models Derived from Point Processes to Species Distributions using 'inlabru'

Integrated species distribution modeling is a rising field in quantitative ecology thanks to significant rises in the quantity of data available, increases in computational speed and the proven benefits of using such models. Despite this, the general software to help ecologists construct such models in an easy-to-use framework is lacking. We therefore introduce the R package 'PointedSDMs': which provides the tools to help ecologists set up integrated models and perform inference on them. There are also functions within the package to help run spatial cross-validation for model selection, as well as generic plotting and predicting functions. An introduction to these methods is discussed in Issac, Jarzyna, Keil, Dambly, Boersch-Supan, Browning, Freeman, Golding, Guillera-Arroita, Henrys, Jarvis, Lahoz-Monfort, Pagel, Pescott, Schmucki, Simmonds and O’Hara (2020) <doi:10.1016/j.tree.2019.08.006>.

Maintained by Philip Mostert. Last updated 2 months ago.

2.8 match 25 stars 8.57 score 50 scripts 1 dependents

cran

propagate:Propagation of Uncertainty

Propagation of uncertainty using higher-order Taylor expansion and Monte Carlo simulation.

Maintained by Andrej-Nikolai Spiess. Last updated 7 years ago.

cpp

4.9 match 2 stars 4.82 score 183 scripts 3 dependents

bioc

scds:In-Silico Annotation of Doublets for Single Cell RNA Sequencing Data

In single cell RNA sequencing (scRNA-seq) data combinations of cells are sometimes considered a single cell (doublets). The scds package provides methods to annotate doublets in scRNA-seq data computationally.

Maintained by Dennis Kostka. Last updated 5 months ago.

singlecell rnaseq qualitycontrol preprocessing transcriptomics geneexpression sequencing software classification

3.6 match 6.57 score 176 scripts 1 dependents

bioc

RCM:Fit row-column association models with the negative binomial distribution for the microbiome

Combine ideas of log-linear analysis of contingency table, flexible response function estimation and empirical Bayes dispersion estimation for explorative visualization of microbiome datasets. The package includes unconstrained as well as constrained analysis. In addition, diagnostic plot to detect lack of fit are available.

Maintained by Stijn Hawinkel. Last updated 5 months ago.

metagenomics dimensionreduction microbiome visualization ordination phyloseq rcm

3.4 match 16 stars 6.90 score 25 scripts

kkholst

mets:Analysis of Multivariate Event Times

Implementation of various statistical models for multivariate event history data <doi:10.1007/s10985-013-9244-x>. Including multivariate cumulative incidence models <doi:10.1002/sim.6016>, and bivariate random effects probit models (Liability models) <doi:10.1016/j.csda.2015.01.014>. Modern methods for survival analysis, including regression modelling (Cox, Fine-Gray, Ghosh-Lin, Binomial regression) with fast computation of influence functions.

Maintained by Klaus K. Holst. Last updated 3 days ago.

multivariate-time-to-event survival-analysis time-to-event fortran openblas cpp

1.8 match 14 stars 13.47 score 236 scripts 42 dependents

julia-wrobel

registr:Curve Registration for Exponential Family Functional Data

A method for performing joint registration and functional principal component analysis for curves (functional data) that are generated from exponential family distributions. This mainly implements the algorithms described in 'Wrobel et al. (2019)' <doi:10.1111/biom.12963> and further adapts them to potentially incomplete curves where (some) curves are not observed from the beginning and/or until the end of the common domain. Curve registration can be used to better understand patterns in functional data by separating curves into phase and amplitude variability. This software handles both binary and continuous functional data, and is especially applicable in accelerometry and wearable technology.

Maintained by Julia Wrobel. Last updated 3 years ago.

openblas cpp

3.8 match 16 stars 6.27 score 29 scripts

catherineschramm

KSPM:Kernel Semi-Parametric Models

To fit the kernel semi-parametric model and its extensions. It allows multiple kernels and unlimited interactions in the same model. Coefficients are estimated by maximizing a penalized log-likelihood; penalization terms and hyperparameters are estimated by minimizing leave-one-out error. It includes predictions with confidence/prediction intervals, statistical tests for the significance of each kernel, a procedure for variable selection and graphical tools for diagnostics and interpretation of covariate effects. Currently it is implemented for continuous dependent variables. The package is based on the paper of Liu et al. (2007), <doi:10.1111/j.1541-0420.2007.00799.x>.

Maintained by Catherine Schramm. Last updated 5 years ago.

10.4 match 2.26 score 18 scripts

stan-dev

StanHeaders:C++ Header Files for Stan

The C++ header files of the Stan project are provided by this package, but it contains little R code or documentation. The main reference is the vignette. There is a shared object containing part of the 'CVODES' library, but its functionality is not accessible from R. 'StanHeaders' is primarily useful for developers who want to utilize the 'LinkingTo' directive of their package's DESCRIPTION file to build on the Stan library without incurring unnecessary dependencies. The Stan project develops a probabilistic programming language that implements full or approximate Bayesian statistical inference via Markov Chain Monte Carlo or 'variational' methods and implements (optionally penalized) maximum likelihood estimation via optimization. The Stan library includes an advanced automatic differentiation scheme, 'templated' statistical and linear algebra functions that can handle the automatically 'differentiable' scalar types (and doubles, 'ints', etc.), and a parser for the Stan language. The 'rstan' package provides user-facing R functions to parse, compile, test, estimate, and analyze Stan models.

Maintained by Ben Goodrich. Last updated 2 days ago.

bayesian-data-analysis bayesian-inference bayesian-statistics mcmc stan

1.5 match 1.1k stars 15.52 score 291 scripts 344 dependents