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igraph

igraph:Network Analysis and Visualization

Routines for simple graphs and network analysis. It can handle large graphs very well and provides functions for generating random and regular graphs, graph visualization, centrality methods and much more.

Maintained by Kirill Müller. Last updated 8 hours ago.

complex-networksgraph-algorithmsgraph-theorymathematicsnetwork-analysisnetwork-graphfortranlibxml2glpkopenblascpp

584 stars 21.14 score 31k scripts 1.9k dependents

vegandevs

vegan:Community Ecology Package

Ordination methods, diversity analysis and other functions for community and vegetation ecologists.

Maintained by Jari Oksanen. Last updated 29 days ago.

ecological-modellingecologyordinationfortranopenblas

472 stars 19.41 score 15k scripts 440 dependents

harrelfe

Hmisc:Harrell Miscellaneous

Contains many functions useful for data analysis, high-level graphics, utility operations, functions for computing sample size and power, simulation, importing and annotating datasets, imputing missing values, advanced table making, variable clustering, character string manipulation, conversion of R objects to LaTeX and html code, recoding variables, caching, simplified parallel computing, encrypting and decrypting data using a safe workflow, general moving window statistical estimation, and assistance in interpreting principal component analysis.

Maintained by Frank E Harrell Jr. Last updated 4 days ago.

fortran

209 stars 17.64 score 17k scripts 750 dependents

andrisignorell

DescTools:Tools for Descriptive Statistics

A collection of miscellaneous basic statistic functions and convenience wrappers for efficiently describing data. The author's intention was to create a toolbox, which facilitates the (notoriously time consuming) first descriptive tasks in data analysis, consisting of calculating descriptive statistics, drawing graphical summaries and reporting the results. The package contains furthermore functions to produce documents using MS Word (or PowerPoint) and functions to import data from Excel. Many of the included functions can be found scattered in other packages and other sources written partly by Titans of R. The reason for collecting them here, was primarily to have them consolidated in ONE instead of dozens of packages (which themselves might depend on other packages which are not needed at all), and to provide a common and consistent interface as far as function and arguments naming, NA handling, recycling rules etc. are concerned. Google style guides were used as naming rules (in absence of convincing alternatives). The 'BigCamelCase' style was consequently applied to functions borrowed from contributed R packages as well.

Maintained by Andri Signorell. Last updated 1 days ago.

fortrancpp

86 stars 16.73 score 7.7k scripts 101 dependents

r-spatial

classInt:Choose Univariate Class Intervals

Selected commonly used methods for choosing univariate class intervals for mapping or other graphics purposes.

Maintained by Roger Bivand. Last updated 3 months ago.

fortran

34 stars 16.17 score 3.2k scripts 1.2k dependents

r-forge

mvtnorm:Multivariate Normal and t Distributions

Computes multivariate normal and t probabilities, quantiles, random deviates, and densities. Log-likelihoods for multivariate Gaussian models and Gaussian copulae parameterised by Cholesky factors of covariance or precision matrices are implemented for interval-censored and exact data, or a mix thereof. Score functions for these log-likelihoods are available. A class representing multiple lower triangular matrices and corresponding methods are part of this package.

Maintained by Torsten Hothorn. Last updated 30 days ago.

fortranopenblas

15.89 score 13k scripts 2.7k 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.

oceanographyfortrancpp

146 stars 15.34 score 4.2k scripts 18 dependents

trevorhastie

glmnet:Lasso and Elastic-Net Regularized Generalized Linear Models

Extremely efficient procedures for fitting the entire lasso or elastic-net regularization path for linear regression, logistic and multinomial regression models, Poisson regression, Cox model, multiple-response Gaussian, and the grouped multinomial regression; see <doi:10.18637/jss.v033.i01> and <doi:10.18637/jss.v039.i05>. There are two new and important additions. The family argument can be a GLM family object, which opens the door to any programmed family (<doi:10.18637/jss.v106.i01>). This comes with a modest computational cost, so when the built-in families suffice, they should be used instead. The other novelty is the relax option, which refits each of the active sets in the path unpenalized. The algorithm uses cyclical coordinate descent in a path-wise fashion, as described in the papers cited.

Maintained by Trevor Hastie. Last updated 2 years ago.

fortrancpp

82 stars 15.15 score 22k scripts 736 dependents

mhahsler

seriation:Infrastructure for Ordering Objects Using Seriation

Infrastructure for ordering objects with an implementation of several seriation/sequencing/ordination techniques to reorder matrices, dissimilarity matrices, and dendrograms. Also provides (optimally) reordered heatmaps, color images and clustering visualizations like dissimilarity plots, and visual assessment of cluster tendency plots (VAT and iVAT). Hahsler et al (2008) <doi:10.18637/jss.v025.i03>.

Maintained by Michael Hahsler. Last updated 3 days ago.

combinatorial-optimizationordinationseriationfortran

77 stars 14.11 score 640 scripts 79 dependents

edzer

hexbin:Hexagonal Binning Routines

Binning and plotting functions for hexagonal bins.

Maintained by Edzer Pebesma. Last updated 5 months ago.

fortran

37 stars 14.00 score 2.4k scripts 114 dependents

rkoenker

quantreg:Quantile Regression

Estimation and inference methods for models for conditional quantile functions: Linear and nonlinear parametric and non-parametric (total variation penalized) models for conditional quantiles of a univariate response and several methods for handling censored survival data. Portfolio selection methods based on expected shortfall risk are also now included. See Koenker, R. (2005) Quantile Regression, Cambridge U. Press, <doi:10.1017/CBO9780511754098> and Koenker, R. et al. (2017) Handbook of Quantile Regression, CRC Press, <doi:10.1201/9781315120256>.

Maintained by Roger Koenker. Last updated 19 days ago.

fortranopenblas

18 stars 13.93 score 2.6k scripts 1.5k dependents

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 9 hours ago.

multivariate-time-to-eventsurvival-analysistime-to-eventfortranopenblascpp

14 stars 13.45 score 236 scripts 42 dependents

r-forge

robustbase:Basic Robust Statistics

"Essential" Robust Statistics. Tools allowing to analyze data with robust methods. This includes regression methodology including model selections and multivariate statistics where we strive to cover the book "Robust Statistics, Theory and Methods" by 'Maronna, Martin and Yohai'; Wiley 2006.

Maintained by Martin Maechler. Last updated 4 months ago.

fortranopenblas

13.38 score 1.7k scripts 480 dependents

eddelbuettel

inline:Functions to Inline C, C++, Fortran Function Calls from R

Functionality to dynamically define R functions and S4 methods with 'inlined' C, C++ or Fortran code supporting the .C and .Call calling conventions.

Maintained by Dirk Eddelbuettel. Last updated 2 months ago.

fortranrcpp

43 stars 13.11 score 576 scripts 333 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

15 stars 12.70 score 7.7k scripts 297 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.

fortranopenblas

12.33 score 8.0k scripts 427 dependents

luca-scr

mclust:Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation

Gaussian finite mixture models fitted via EM algorithm for model-based clustering, classification, and density estimation, including Bayesian regularization, dimension reduction for visualisation, and resampling-based inference.

Maintained by Luca Scrucca. Last updated 11 months ago.

fortranopenblas

21 stars 12.23 score 6.6k scripts 587 dependents

andyliaw-mrk

randomForest:Breiman and Cutlers Random Forests for Classification and Regression

Classification and regression based on a forest of trees using random inputs, based on Breiman (2001) <DOI:10.1023/A:1010933404324>.

Maintained by Andy Liaw. Last updated 6 months ago.

fortran

46 stars 12.23 score 35k scripts 282 dependents

jinghuazhao

gap:Genetic Analysis Package

As first reported [Zhao, J. H. 2007. "gap: Genetic Analysis Package". J Stat Soft 23(8):1-18. <doi:10.18637/jss.v023.i08>], it is designed as an integrated package for genetic data analysis of both population and family data. Currently, it contains functions for sample size calculations of both population-based and family-based designs, probability of familial disease aggregation, kinship calculation, statistics in linkage analysis, and association analysis involving genetic markers including haplotype analysis with or without environmental covariates. Over years, the package has been developed in-between many projects hence also in line with the name (gap).

Maintained by Jing Hua Zhao. Last updated 4 days ago.

geneticsimputationlmmfortran

12 stars 11.94 score 448 scripts 16 dependents

r-forge

expm:Matrix Exponential, Log, 'etc'

Computation of the matrix exponential, logarithm, sqrt, and related quantities, using traditional and modern methods.

Maintained by Martin Maechler. Last updated 5 months ago.

fortranopenblas

11.91 score 1.3k scripts 432 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 3 months ago.

fortrancpp

1 stars 11.73 score 227 scripts 1.7k dependents

opendendro

dplR:Dendrochronology Program Library in R

Perform tree-ring analyses such as detrending, chronology building, and cross dating. Read and write standard file formats used in dendrochronology.

Maintained by Andy Bunn. Last updated 1 months ago.

fortran

40 stars 11.66 score 546 scripts 26 dependents

rudjer

SparseM:Sparse Linear Algebra

Some basic linear algebra functionality for sparse matrices is provided: including Cholesky decomposition and backsolving as well as standard R subsetting and Kronecker products.

Maintained by Roger Koenker. Last updated 9 months ago.

fortran

3 stars 11.47 score 306 scripts 1.5k dependents

cecileproust-lima

lcmm:Extended Mixed Models Using Latent Classes and Latent Processes

Estimation of various extensions of the mixed models including latent class mixed models, joint latent class mixed models, mixed models for curvilinear outcomes, mixed models for multivariate longitudinal outcomes using a maximum likelihood estimation method (Proust-Lima, Philipps, Liquet (2017) <doi:10.18637/jss.v078.i02>).

Maintained by Cecile Proust-Lima. Last updated 2 months ago.

fortran

62 stars 11.41 score 249 scripts 7 dependents

kurthornik

tseries:Time Series Analysis and Computational Finance

Time series analysis and computational finance.

Maintained by Kurt Hornik. Last updated 6 months ago.

fortranopenblas

4 stars 11.29 score 10k scripts 289 dependents

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 1 months ago.

fortranopenblascppopenmp

40 stars 11.24 score 220 scripts 13 dependents

bioc

Rhdf5lib:hdf5 library as an R package

Provides C and C++ hdf5 libraries.

Maintained by Mike Smith. Last updated 6 days ago.

infrastructurebioconductorhdf5hdf5-libraryfortranzlib

6 stars 11.22 score 26 scripts 341 dependents

adeverse

adespatial:Multivariate Multiscale Spatial Analysis

Tools for the multiscale spatial analysis of multivariate data. Several methods are based on the use of a spatial weighting matrix and its eigenvector decomposition (Moran's Eigenvectors Maps, MEM). Several approaches are described in the review Dray et al (2012) <doi:10.1890/11-1183.1>.

Maintained by Aurélie Siberchicot. Last updated 9 days ago.

fortranopenblas

36 stars 11.16 score 398 scripts 2 dependents

bioc

genefilter:genefilter: methods for filtering genes from high-throughput experiments

Some basic functions for filtering genes.

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

microarrayfortrancpp

11.11 score 2.4k scripts 143 dependents

mclements

rstpm2:Smooth Survival Models, Including Generalized Survival Models

R implementation of generalized survival models (GSMs), smooth accelerated failure time (AFT) models and Markov multi-state models. For the GSMs, g(S(t|x))=eta(t,x) for a link function g, survival S at time t with covariates x and a linear predictor eta(t,x). The main assumption is that the time effect(s) are smooth <doi:10.1177/0962280216664760>. For fully parametric models with natural splines, this re-implements Stata's 'stpm2' function, which are flexible parametric survival models developed by Royston and colleagues. We have extended the parametric models to include any smooth parametric smoothers for time. We have also extended the model to include any smooth penalized smoothers from the 'mgcv' package, using penalized likelihood. These models include left truncation, right censoring, interval censoring, gamma frailties and normal random effects <doi:10.1002/sim.7451>, and copulas. For the smooth AFTs, S(t|x) = S_0(t*eta(t,x)), where the baseline survival function S_0(t)=exp(-exp(eta_0(t))) is modelled for natural splines for eta_0, and the time-dependent cumulative acceleration factor eta(t,x)=\int_0^t exp(eta_1(u,x)) du for log acceleration factor eta_1(u,x). The Markov multi-state models allow for a range of models with smooth transitions to predict transition probabilities, length of stay, utilities and costs, with differences, ratios and standardisation.

Maintained by Mark Clements. Last updated 5 months ago.

fortranopenblascpp

27 stars 11.09 score 137 scripts 52 dependents

bnaras

cubature:Adaptive Multivariate Integration over Hypercubes

R wrappers around the cubature C library of Steven G. Johnson for adaptive multivariate integration over hypercubes and the Cuba C library of Thomas Hahn for deterministic and Monte Carlo integration. Scalar and vector interfaces for cubature and Cuba routines are provided; the vector interfaces are highly recommended as demonstrated in the package vignette.

Maintained by Balasubramanian Narasimhan. Last updated 9 months ago.

fortrancpp

12 stars 11.08 score 488 scripts 162 dependents

helske

KFAS:Kalman Filter and Smoother for Exponential Family State Space Models

State space modelling is an efficient and flexible framework for statistical inference of a broad class of time series and other data. KFAS includes computationally efficient functions for Kalman filtering, smoothing, forecasting, and simulation of multivariate exponential family state space models, with observations from Gaussian, Poisson, binomial, negative binomial, and gamma distributions. See the paper by Helske (2017) <doi:10.18637/jss.v078.i10> for details.

Maintained by Jouni Helske. Last updated 7 months ago.

dynamic-linear-modelexponential-familyfortrangaussian-modelsstate-spacetime-seriesopenblas

64 stars 10.97 score 242 scripts 16 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 2 months ago.

fortran

10 stars 10.67 score 3.6k scripts 169 dependents

merliseclyde

BAS:Bayesian Variable Selection and Model Averaging using Bayesian Adaptive Sampling

Package for Bayesian Variable Selection and Model Averaging in linear models and generalized linear models using stochastic or deterministic sampling without replacement from posterior distributions. Prior distributions on coefficients are from Zellner's g-prior or mixtures of g-priors corresponding to the Zellner-Siow Cauchy Priors or the mixture of g-priors from Liang et al (2008) <DOI:10.1198/016214507000001337> for linear models or mixtures of g-priors from Li and Clyde (2019) <DOI:10.1080/01621459.2018.1469992> in generalized linear models. Other model selection criteria include AIC, BIC and Empirical Bayes estimates of g. Sampling probabilities may be updated based on the sampled models using sampling w/out replacement or an efficient MCMC algorithm which samples models using a tree structure of the model space as an efficient hash table. See Clyde, Ghosh and Littman (2010) <DOI:10.1198/jcgs.2010.09049> for details on the sampling algorithms. Uniform priors over all models or beta-binomial prior distributions on model size are allowed, and for large p truncated priors on the model space may be used to enforce sampling models that are full rank. The user may force variables to always be included in addition to imposing constraints that higher order interactions are included only if their parents are included in the model. This material is based upon work supported by the National Science Foundation under Division of Mathematical Sciences grant 1106891. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

Maintained by Merlise Clyde. Last updated 4 months ago.

bayesianbayesian-inferencegeneralized-linear-modelslinear-regressionlogistic-regressionmcmcmodel-selectionpoisson-regressionpredictive-modelingregressionvariable-selectionfortranopenblas

44 stars 10.63 score 420 scripts 3 dependents

valentint

rrcov:Scalable Robust Estimators with High Breakdown Point

Robust Location and Scatter Estimation and Robust Multivariate Analysis with High Breakdown Point: principal component analysis (Filzmoser and Todorov (2013), <doi:10.1016/j.ins.2012.10.017>), linear and quadratic discriminant analysis (Todorov and Pires (2007)), multivariate tests (Todorov and Filzmoser (2010) <doi:10.1016/j.csda.2009.08.015>), outlier detection (Todorov et al. (2010) <doi:10.1007/s11634-010-0075-2>). See also Todorov and Filzmoser (2009) <urn:isbn:978-3838108148>, Todorov and Filzmoser (2010) <doi:10.18637/jss.v032.i03> and Boudt et al. (2019) <doi:10.1007/s11222-019-09869-x>.

Maintained by Valentin Todorov. Last updated 7 months ago.

fortranopenblas

2 stars 10.57 score 484 scripts 96 dependents

wrathematics

float:32-Bit Floats

R comes with a suite of utilities for linear algebra with "numeric" (double precision) vectors/matrices. However, sometimes single precision (or less!) is more than enough for a particular task. This package extends R's linear algebra facilities to include 32-bit float (single precision) data. Float vectors/matrices have half the precision of their "numeric"-type counterparts but are generally faster to numerically operate on, for a performance vs accuracy trade-off. The internal representation is an S4 class, which allows us to keep the syntax identical to that of base R's. Interaction between floats and base types for binary operators is generally possible; in these cases, type promotion always defaults to the higher precision. The package ships with copies of the single precision 'BLAS' and 'LAPACK', which are automatically built in the event they are not available on the system.

Maintained by Drew Schmidt. Last updated 20 days ago.

float-matrixhpclinear-algebramatrixfortranopenblasopenmp

46 stars 10.53 score 228 scripts 42 dependents

robjhyndman

hdrcde:Highest Density Regions and Conditional Density Estimation

Computation of highest density regions in one and two dimensions, kernel estimation of univariate density functions conditional on one covariate,and multimodal regression.

Maintained by Rob Hyndman. Last updated 2 years ago.

fortran

24 stars 10.38 score 128 scripts 158 dependents

berwinturlach

quadprog:Functions to Solve Quadratic Programming Problems

This package contains routines and documentation for solving quadratic programming problems.

Maintained by Berwin A. Turlach. Last updated 5 years ago.

fortranopenblas

3 stars 10.33 score 972 scripts 1.2k dependents

tslumley

leaps:Regression Subset Selection

Regression subset selection, including exhaustive search.

Maintained by Thomas Lumley. Last updated 10 months ago.

fortran

8 stars 10.29 score 4.5k scripts 171 dependents

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 16 days ago.

robustrobust-estimationrobust-regressionrobust-statisticsrobustnessstatisticsfortranopenblas

17 stars 10.23 score 84 scripts 8 dependents

cran

nlme:Linear and Nonlinear Mixed Effects Models

Fit and compare Gaussian linear and nonlinear mixed-effects models.

Maintained by R Core Team. Last updated 2 months ago.

fortran

6 stars 9.77 score 8.8k dependents

goranbrostrom

eha:Event History Analysis

Parametric proportional hazards fitting with left truncation and right censoring for common families of distributions, piecewise constant hazards, and discrete models. Parametric accelerated failure time models for left truncated and right censored data. Proportional hazards models for tabular and register data. Sampling of risk sets in Cox regression, selections in the Lexis diagram, bootstrapping. Broström (2022) <doi:10.1201/9780429503764>.

Maintained by Göran Broström. Last updated 10 months ago.

fortranopenblas

7 stars 9.76 score 308 scripts 10 dependents

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 5 months ago.

functional-data-analysisfortran

12 stars 9.72 score 560 scripts 22 dependents

pecanproject

PEcAnRTM:PEcAn Functions Used for Radiative Transfer Modeling

Functions for performing forward runs and inversions of radiative transfer models (RTMs). Inversions can be performed using maximum likelihood, or more complex hierarchical Bayesian methods. Underlying numerical analyses are optimized for speed using Fortran code.

Maintained by Alexey Shiklomanov. Last updated 3 days ago.

bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplantsfortranjagscpp

216 stars 9.70 score 132 scripts

gksmyth

statmod:Statistical Modeling

A collection of algorithms and functions to aid statistical modeling. Includes limiting dilution analysis (aka ELDA), growth curve comparisons, mixed linear models, heteroscedastic regression, inverse-Gaussian probability calculations, Gauss quadrature and a secure convergence algorithm for nonlinear models. Also includes advanced generalized linear model functions including Tweedie and Digamma distributional families, secure convergence and exact distributional calculations for unit deviances.

Maintained by Gordon Smyth. Last updated 2 years ago.

fortran

1 stars 9.62 score 2.2k scripts 849 dependents

karlines

rootSolve:Nonlinear Root Finding, Equilibrium and Steady-State Analysis of Ordinary Differential Equations

Routines to find the root of nonlinear functions, and to perform steady-state and equilibrium analysis of ordinary differential equations (ODE). Includes routines that: (1) generate gradient and jacobian matrices (full and banded), (2) find roots of non-linear equations by the 'Newton-Raphson' method, (3) estimate steady-state conditions of a system of (differential) equations in full, banded or sparse form, using the 'Newton-Raphson' method, or by dynamically running, (4) solve the steady-state conditions for uni-and multicomponent 1-D, 2-D, and 3-D partial differential equations, that have been converted to ordinary differential equations by numerical differencing (using the method-of-lines approach). Includes fortran code.

Maintained by Karline Soetaert. Last updated 2 years ago.

fortran

1 stars 9.61 score 1.2k scripts 216 dependents

trevorhastie

gam:Generalized Additive Models

Functions for fitting and working with generalized additive models, as described in chapter 7 of "Statistical Models in S" (Chambers and Hastie (eds), 1991), and "Generalized Additive Models" (Hastie and Tibshirani, 1990).

Maintained by Trevor Hastie. Last updated 7 months ago.

fortranopenblas

4 stars 9.50 score 2.2k scripts 61 dependents

bioc

DNAcopy:DNA Copy Number Data Analysis

Implements the circular binary segmentation (CBS) algorithm to segment DNA copy number data and identify genomic regions with abnormal copy number.

Maintained by Venkatraman E. Seshan. Last updated 5 months ago.

microarraycopynumbervariationfortran

9.49 score 233 scripts 64 dependents

r-forge

CHNOSZ:Thermodynamic Calculations and Diagrams for Geochemistry

An integrated set of tools for thermodynamic calculations in aqueous geochemistry and geobiochemistry. Functions are provided for writing balanced reactions to form species from user-selected basis species and for calculating the standard molal properties of species and reactions, including the standard Gibbs energy and equilibrium constant. Calculations of the non-equilibrium chemical affinity and equilibrium chemical activity of species can be portrayed on diagrams as a function of temperature, pressure, or activity of basis species; in two dimensions, this gives a maximum affinity or predominance diagram. The diagrams have formatted chemical formulas and axis labels, and water stability limits can be added to Eh-pH, oxygen fugacity- temperature, and other diagrams with a redox variable. The package has been developed to handle common calculations in aqueous geochemistry, such as solubility due to complexation of metal ions, mineral buffers of redox or pH, and changing the basis species across a diagram ("mosaic diagrams"). CHNOSZ also implements a group additivity algorithm for the standard thermodynamic properties of proteins.

Maintained by Jeffrey Dick. Last updated 21 days ago.

fortran

9.46 score 238 scripts 4 dependents

hanase

BMA:Bayesian Model Averaging

Package for Bayesian model averaging and variable selection for linear models, generalized linear models and survival models (cox regression).

Maintained by Hana Sevcikova. Last updated 2 months ago.

fortran

38 stars 9.40 score 152 scripts 14 dependents

reinhardfurrer

spam:SPArse Matrix

Set of functions for sparse matrix algebra. Differences with other sparse matrix packages are: (1) we only support (essentially) one sparse matrix format, (2) based on transparent and simple structure(s), (3) tailored for MCMC calculations within G(M)RF. (4) and it is fast and scalable (with the extension package spam64). Documentation about 'spam' is provided by vignettes included in this package, see also Furrer and Sain (2010) <doi:10.18637/jss.v036.i10>; see 'citation("spam")' for details.

Maintained by Reinhard Furrer. Last updated 2 months ago.

fortranopenblascpp

1 stars 9.36 score 420 scripts 439 dependents

hdakpo

ucminf:General-Purpose Unconstrained Non-Linear Optimization

An algorithm for general-purpose unconstrained non-linear optimization. The algorithm is of quasi-Newton type with BFGS updating of the inverse Hessian and soft line search with a trust region type monitoring of the input to the line search algorithm. The interface of 'ucminf' is designed for easy interchange with 'optim'.

Maintained by K Hervé Dakpo. Last updated 9 months ago.

fortranopenblas

3 stars 9.24 score 155 scripts 204 dependents

cole-trapnell-lab

leidenbase:R and C/C++ Wrappers to Run the Leiden find_partition() Function

An R to C/C++ interface that runs the Leiden community detection algorithm to find a basic partition (). It runs the equivalent of the 'leidenalg' find_partition() function, which is given in the 'leidenalg' distribution file 'leiden/src/functions.py'. This package includes the required source code files from the official 'leidenalg' distribution and functions from the R 'igraph' package. The 'leidenalg' distribution is available from <https://github.com/vtraag/leidenalg/> and the R 'igraph' package is available from <https://igraph.org/r/>. The Leiden algorithm is described in the article by Traag et al. (2019) <doi:10.1038/s41598-019-41695-z>. Leidenbase includes code from the packages: igraph version 0.9.8 with license GPL (>= 2), leidenalg version 0.8.10 with license GPL 3.

Maintained by Brent Ewing. Last updated 2 months ago.

fortranlibxml2glpkopenblascpp

13 stars 9.15 score 44 scripts 77 dependents

bioc

impute:impute: Imputation for microarray data

Imputation for microarray data (currently KNN only)

Maintained by Balasubramanian Narasimhan. Last updated 5 months ago.

microarrayfortran

9.05 score 952 scripts 133 dependents

bpfaff

urca:Unit Root and Cointegration Tests for Time Series Data

Unit root and cointegration tests encountered in applied econometric analysis are implemented.

Maintained by Bernhard Pfaff. Last updated 10 months ago.

fortran

6 stars 8.95 score 1.4k scripts 270 dependents

geco-bern

rsofun:The P-Model and BiomeE Modelling Framework

Implements the Simulating Optimal FUNctioning framework for site-scale simulations of ecosystem processes, including model calibration. It contains 'Fortran 90' modules for the P-model (Stocker et al. (2020) <doi:10.5194/gmd-13-1545-2020>), SPLASH (Davis et al. (2017) <doi:10.5194/gmd-10-689-2017>) and BiomeE (Weng et al. (2015) <doi:10.5194/bg-12-2655-2015>).

Maintained by Benjamin Stocker. Last updated 1 days ago.

dgvmgrowthmodelingp-modelsimulationvegetation-dynamicsfortran

27 stars 8.85 score 119 scripts

stefanwilhelm

tmvtnorm:Truncated Multivariate Normal and Student t Distribution

Random number generation for the truncated multivariate normal and Student t distribution. Computes probabilities, quantiles and densities, including one-dimensional and bivariate marginal densities. Computes first and second moments (i.e. mean and covariance matrix) for the double-truncated multinormal case.

Maintained by Stefan Wilhelm. Last updated 1 years ago.

fortranopenblas

1 stars 8.84 score 338 scripts 59 dependents

asl

svd:Interfaces to Various State-of-Art SVD and Eigensolvers

R bindings to SVD and eigensolvers (PROPACK, nuTRLan).

Maintained by Anton Korobeynikov. Last updated 3 months ago.

fortranopenblas

27 stars 8.80 score 244 scripts 30 dependents

r-forge

signal:Signal Processing

A set of signal processing functions originally written for 'Matlab' and 'Octave'. Includes filter generation utilities, filtering functions, resampling routines, and visualization of filter models. It also includes interpolation functions.

Maintained by Uwe Ligges. Last updated 1 years ago.

fortran

8.78 score 828 scripts 151 dependents

pchausse

gmm:Generalized Method of Moments and Generalized Empirical Likelihood

It is a complete suite to estimate models based on moment conditions. It includes the two step Generalized method of moments (Hansen 1982; <doi:10.2307/1912775>), the iterated GMM and continuous updated estimator (Hansen, Eaton and Yaron 1996; <doi:10.2307/1392442>) and several methods that belong to the Generalized Empirical Likelihood family of estimators (Smith 1997; <doi:10.1111/j.0013-0133.1997.174.x>, Kitamura 1997; <doi:10.1214/aos/1069362388>, Newey and Smith 2004; <doi:10.1111/j.1468-0262.2004.00482.x>, and Anatolyev 2005 <doi:10.1111/j.1468-0262.2005.00601.x>).

Maintained by Pierre Chausse. Last updated 1 years ago.

fortranopenblas

2 stars 8.75 score 304 scripts 65 dependents

rsbivand

splancs:Spatial and Space-Time Point Pattern Analysis

The Splancs package was written as an enhancement to S-Plus for display and analysis of spatial point pattern data; it has been ported to R and is in "maintenance mode".

Maintained by Roger Bivand. Last updated 10 months ago.

fortran

1 stars 8.75 score 592 scripts 53 dependents

atmoschem

vein:Vehicular Emissions Inventories

Elaboration of vehicular emissions inventories, consisting in four stages, pre-processing activity data, preparing emissions factors, estimating the emissions and post-processing of emissions in maps and databases. More details in Ibarra-Espinosa et al (2018) <doi:10.5194/gmd-11-2209-2018>. Before using VEIN you need to know the vehicular composition of your study area, in other words, the combination of of type of vehicles, size and fuel of the fleet. Then, it is recommended to start with the project to download a template to create a structure of directories and scripts.

Maintained by Sergio Ibarra-Espinosa. Last updated 16 hours ago.

atmoschematmospheric-chemistryatmospheric-scienceatmospheric-sciencesemissionsemissions-modelvehicular-emissions-inventoriesveinfortranopenmp

46 stars 8.73 score 137 scripts

r-forge

FME:A Flexible Modelling Environment for Inverse Modelling, Sensitivity, Identifiability and Monte Carlo Analysis

Provides functions to help in fitting models to data, to perform Monte Carlo, sensitivity and identifiability analysis. It is intended to work with models be written as a set of differential equations that are solved either by an integration routine from package 'deSolve', or a steady-state solver from package 'rootSolve'. However, the methods can also be used with other types of functions.

Maintained by Karline Soetaert. Last updated 2 years ago.

fortran

8.62 score 382 scripts 9 dependents

rsetienne

DAISIE:Dynamical Assembly of Islands by Speciation, Immigration and Extinction

Simulates and computes the (maximum) likelihood of a dynamical model of island biota assembly through speciation, immigration and extinction. See Valente et al. (2015) <doi:10.1111/ele.12461>.

Maintained by Rampal S. Etienne. Last updated 2 months ago.

fortrancpp

9 stars 8.59 score 55 scripts 1 dependents

martin3141

spant:MR Spectroscopy Analysis Tools

Tools for reading, visualising and processing Magnetic Resonance Spectroscopy data. The package includes methods for spectral fitting: Wilson (2021) <DOI:10.1002/mrm.28385> and spectral alignment: Wilson (2018) <DOI:10.1002/mrm.27605>.

Maintained by Martin Wilson. Last updated 1 days ago.

brainmrimrsmrshubspectroscopyfortran

25 stars 8.52 score 81 scripts

brentonk

pbivnorm:Vectorized Bivariate Normal CDF

Provides a vectorized R function for calculating probabilities from a standard bivariate normal CDF.

Maintained by Brenton Kenkel. Last updated 10 years ago.

fortran

2 stars 8.42 score 89 scripts 242 dependents

stephenmilborrow

earth:Multivariate Adaptive Regression Splines

Build regression models using the techniques in Friedman's papers "Fast MARS" and "Multivariate Adaptive Regression Splines" <doi:10.1214/aos/1176347963>. (The term "MARS" is trademarked and thus not used in the name of the package.)

Maintained by Stephen Milborrow. Last updated 6 months ago.

fortranopenblas

5 stars 8.40 score 3.9k scripts 26 dependents

muvisu

biplotEZ:EZ-to-Use Biplots

Provides users with an EZ-to-use platform for representing data with biplots. Currently principal component analysis (PCA), canonical variate analysis (CVA) and simple correspondence analysis (CA) biplots are included. This is accompanied by various formatting options for the samples and axes. Alpha-bags and concentration ellipses are included for visual enhancements and interpretation. For an extensive discussion on the topic, see Gower, J.C., Lubbe, S. and le Roux, N.J. (2011, ISBN: 978-0-470-01255-0) Understanding Biplots. Wiley: Chichester.

Maintained by Sugnet Lubbe. Last updated 19 days ago.

fortran

7 stars 8.39 score 30 scripts 1 dependents

swihart

rmutil:Utilities for Nonlinear Regression and Repeated Measurements Models

A toolkit of functions for nonlinear regression and repeated measurements not to be used by itself but called by other Lindsey packages such as 'gnlm', 'stable', 'growth', 'repeated', and 'event' (available at <https://www.commanster.eu/rcode.html>).

Maintained by Bruce Swihart. Last updated 2 years ago.

fortran

1 stars 8.35 score 358 scripts 70 dependents

cjvanlissa

bain:Bayes Factors for Informative Hypotheses

Computes approximated adjusted fractional Bayes factors for equality, inequality, and about equality constrained hypotheses. For a tutorial on this method, see Hoijtink, Mulder, van Lissa, & Gu, (2019) <doi:10.1037/met0000201>. For applications in structural equation modeling, see: Van Lissa, Gu, Mulder, Rosseel, Van Zundert, & Hoijtink, (2021) <doi:10.1080/10705511.2020.1745644>. For the statistical underpinnings, see Gu, Mulder, and Hoijtink (2018) <doi:10.1111/bmsp.12110>; Hoijtink, Gu, & Mulder, J. (2019) <doi:10.1111/bmsp.12145>; Hoijtink, Gu, Mulder, & Rosseel, (2019) <doi:10.31234/osf.io/q6h5w>.

Maintained by Caspar J van Lissa. Last updated 10 months ago.

fortran

9 stars 8.27 score 67 scripts 8 dependents

jomulder

BFpack:Flexible Bayes Factor Testing of Scientific Expectations

Implementation of default Bayes factors for testing statistical hypotheses under various statistical models. The package is intended for applied quantitative researchers in the social and behavioral sciences, medical research, and related fields. The Bayes factor tests can be executed for statistical models such as univariate and multivariate normal linear models, correlation analysis, generalized linear models, special cases of linear mixed models, survival models, relational event models. Parameters that can be tested are location parameters (e.g., group means, regression coefficients), variances (e.g., group variances), and measures of association (e.g,. polychoric/polyserial/biserial/tetrachoric/product moments correlations), among others. The statistical underpinnings are described in O'Hagan (1995) <DOI:10.1111/j.2517-6161.1995.tb02017.x>, De Santis and Spezzaferri (2001) <DOI:10.1016/S0378-3758(00)00240-8>, Mulder and Xin (2022) <DOI:10.1080/00273171.2021.1904809>, Mulder and Gelissen (2019) <DOI:10.1080/02664763.2021.1992360>, Mulder (2016) <DOI:10.1016/j.jmp.2014.09.004>, Mulder and Fox (2019) <DOI:10.1214/18-BA1115>, Mulder and Fox (2013) <DOI:10.1007/s11222-011-9295-3>, Boeing-Messing, van Assen, Hofman, Hoijtink, and Mulder (2017) <DOI:10.1037/met0000116>, Hoijtink, Mulder, van Lissa, and Gu (2018) <DOI:10.1037/met0000201>, Gu, Mulder, and Hoijtink (2018) <DOI:10.1111/bmsp.12110>, Hoijtink, Gu, and Mulder (2018) <DOI:10.1111/bmsp.12145>, and Hoijtink, Gu, Mulder, and Rosseel (2018) <DOI:10.1037/met0000187>. When using the packages, please refer to the package Mulder et al. (2021) <DOI:10.18637/jss.v100.i18> and the relevant methodological papers.

Maintained by Joris Mulder. Last updated 2 months ago.

fortranopenblas

15 stars 8.24 score 55 scripts 3 dependents

rpact-com

rpact:Confirmatory Adaptive Clinical Trial Design and Analysis

Design and analysis of confirmatory adaptive clinical trials with continuous, binary, and survival endpoints according to the methods described in the monograph by Wassmer and Brannath (2016) <doi:10.1007/978-3-319-32562-0>. This includes classical group sequential as well as multi-stage adaptive hypotheses tests that are based on the combination testing principle.

Maintained by Friedrich Pahlke. Last updated 5 days ago.

adaptive-designanalysisclinical-trialscount-datagroup-sequential-designspower-calculationsample-size-calculationsimulationvalidatedfortrancpp

25 stars 8.20 score 110 scripts 1 dependents

cran

KernSmooth:Functions for Kernel Smoothing Supporting Wand & Jones (1995)

Functions for kernel smoothing (and density estimation) corresponding to the book: Wand, M.P. and Jones, M.C. (1995) "Kernel Smoothing".

Maintained by Brian Ripley. Last updated 3 months ago.

fortranopenblas

1 stars 8.19 score 2.5k dependents

archer-yang-lab

gglasso:Group Lasso Penalized Learning Using a Unified BMD Algorithm

A unified algorithm, blockwise-majorization-descent (BMD), for efficiently computing the solution paths of the group-lasso penalized least squares, logistic regression, Huberized SVM and squared SVM. The package is an implementation of Yang, Y. and Zou, H. (2015) DOI: <doi:10.1007/s11222-014-9498-5>.

Maintained by Yi Yang. Last updated 5 years ago.

fortran

10 stars 8.12 score 292 scripts 10 dependents

kingaa

subplex:Unconstrained Optimization using the Subplex Algorithm

The subplex algorithm for unconstrained optimization, developed by Tom Rowan.

Maintained by Aaron A. King. Last updated 5 months ago.

numerical-optimizationoptimizationfortranopenblas

10 stars 8.08 score 55 scripts 46 dependents

hsbadr

HiClimR:Hierarchical Climate Regionalization

A tool for Hierarchical Climate Regionalization applicable to any correlation-based clustering. It adds several features and a new clustering method (called, 'regional' linkage) to hierarchical clustering in R ('hclust' function in 'stats' library): data regridding, coarsening spatial resolution, geographic masking, contiguity-constrained clustering, data filtering by mean and/or variance thresholds, data preprocessing (detrending, standardization, and PCA), faster correlation function with preliminary big data support, different clustering methods, hybrid hierarchical clustering, multivariate clustering (MVC), cluster validation, visualization of regionalization results, and exporting region map and mean timeseries into NetCDF-4 file. The technical details are described in Badr et al. (2015) <doi:10.1007/s12145-015-0221-7>.

Maintained by Hamada S. Badr. Last updated 3 months ago.

clusteringcontiguityhomogeneitymultivariateregionalizationspatiotemporalfortran

16 stars 8.06 score 53 scripts 3 dependents

trevorhastie

lars:Least Angle Regression, Lasso and Forward Stagewise

Efficient procedures for fitting an entire lasso sequence with the cost of a single least squares fit. Least angle regression and infinitesimal forward stagewise regression are related to the lasso, as described in the paper below.

Maintained by Trevor Hastie. Last updated 3 years ago.

fortran

6 stars 7.98 score 700 scripts 78 dependents

plangfelder

flashClust:Implementation of optimal hierarchical clustering

Fast implementation of hierarchical clustering

Maintained by Peter Langfelder. Last updated 13 years ago.

fortran

7.96 score 514 scripts 116 dependents

veseshan

clinfun:Clinical Trial Design and Data Analysis Functions

Utilities to make your clinical collaborations easier if not fun. It contains functions for designing studies such as Simon 2-stage and group sequential designs and for data analysis such as Jonckheere-Terpstra test and estimating survival quantiles.

Maintained by Venkatraman E. Seshan. Last updated 1 years ago.

fortran

5 stars 7.86 score 124 scripts 8 dependents

jinghuazhao

pan:Multiple Imputation for Multivariate Panel or Clustered Data

It provides functions and examples for maximum likelihood estimation for generalized linear mixed models and Gibbs sampler for multivariate linear mixed models with incomplete data, as described in Schafer JL (1997) "Imputation of missing covariates under a multivariate linear mixed model". Technical report 97-04, Dept. of Statistics, The Pennsylvania State University.

Maintained by Jing hua Zhao. Last updated 2 years ago.

fortran

1 stars 7.86 score 65 scripts 155 dependents

karlines

limSolve:Solving Linear Inverse Models

Functions that (1) find the minimum/maximum of a linear or quadratic function: min or max (f(x)), where f(x) = ||Ax-b||^2 or f(x) = sum(a_i*x_i) subject to equality constraints Ex=f and/or inequality constraints Gx>=h, (2) sample an underdetermined- or overdetermined system Ex=f subject to Gx>=h, and if applicable Ax~=b, (3) solve a linear system Ax=B for the unknown x. It includes banded and tridiagonal linear systems.

Maintained by Karline Soetaert. Last updated 1 years ago.

fortranopenblas

4 stars 7.85 score 158 scripts 52 dependents

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.

fortrancpp

1 stars 7.76 score 287 dependents

mhahsler

qap:Heuristics for the Quadratic Assignment Problem (QAP)

Implements heuristics for the Quadratic Assignment Problem (QAP). Although, the QAP was introduced as a combinatorial optimization problem for the facility location problem in operations research, it also has many applications in data analysis. The problem is NP-hard and the package implements a simulated annealing heuristic.

Maintained by Michael Hahsler. Last updated 7 months ago.

combinatorial-optimizationheuristicqapquadratic-assignment-problemfortran

6 stars 7.75 score 7 scripts 80 dependents

antoinelucas64

amap:Another Multidimensional Analysis Package

Tools for Clustering and Principal Component Analysis (With robust methods, and parallelized functions).

Maintained by Antoine Lucas. Last updated 5 months ago.

fortrancpp

7.73 score 460 scripts 26 dependents

scottkosty

bootstrap:Functions for the Book "An Introduction to the Bootstrap"

Software (bootstrap, cross-validation, jackknife) and data for the book "An Introduction to the Bootstrap" by B. Efron and R. Tibshirani, 1993, Chapman and Hall. This package is primarily provided for projects already based on it, and for support of the book. New projects should preferentially use the recommended package "boot".

Maintained by Scott Kostyshak. Last updated 6 years ago.

fortran

7.62 score 890 scripts 30 dependents

krahim

multitaper:Spectral Analysis Tools using the Multitaper Method

Implements multitaper spectral analysis using discrete prolate spheroidal sequences (Slepians) and sine tapers. It includes an adaptive weighted multitaper spectral estimate, a coherence estimate, Thomson's Harmonic F-test, and complex demodulation. The Slepians sequences are generated efficiently using a tridiagonal matrix solution, and jackknifed confidence intervals are available for most estimates. This package is an implementation of the method described in D.J. Thomson (1982) "Spectrum estimation and harmonic analysis" <doi:10.1109/PROC.1982.12433>.

Maintained by Karim Rahim. Last updated 9 months ago.

fortranopenblas

10 stars 7.62 score 67 scripts 26 dependents

trevorhastie

mda:Mixture and Flexible Discriminant Analysis

Mixture and flexible discriminant analysis, multivariate adaptive regression splines (MARS), BRUTO, and vector-response smoothing splines. Hastie, Tibshirani and Friedman (2009) "Elements of Statistical Learning (second edition, chap 12)" Springer, New York.

Maintained by Trevor Hastie. Last updated 5 months ago.

fortran

3 stars 7.60 score 428 scripts 17 dependents

pecanproject

PEcAn.BASGRA:PEcAn Package for Integration of the BASGRA Model

This module provides functions to link the BASGRA model to PEcAn.

Maintained by Istem Fer. Last updated 3 days ago.

bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplantsfortranglibc

216 stars 7.58 score 1 scripts

peterkdunn

tweedie:Evaluation of Tweedie Exponential Family Models

Maximum likelihood computations for Tweedie families, including the series expansion (Dunn and Smyth, 2005; <doi:10.1007/s11222-005-4070-y>) and the Fourier inversion (Dunn and Smyth, 2008; <doi:10.1007/s11222-007-9039-6>), and related methods.

Maintained by Peter K. Dunn. Last updated 2 months ago.

fortran

7.57 score 261 scripts 19 dependents

valentint

robust:Port of the S+ "Robust Library"

Methods for robust statistics, a state of the art in the early 2000s, notably for robust regression and robust multivariate analysis.

Maintained by Valentin Todorov. Last updated 7 months ago.

fortranopenblas

7.52 score 572 scripts 8 dependents

x13org

x13binary:Provide the 'x13ashtml' Seasonal Adjustment Binary

The US Census Bureau provides a seasonal adjustment program now called 'X-13ARIMA-SEATS' building on both earlier programs called X-11 and X-12 as well as the SEATS program by the Bank of Spain. The US Census Bureau offers both source and binary versions -- which this package integrates for use by other R packages.

Maintained by Dirk Eddelbuettel. Last updated 8 months ago.

fortran

10 stars 7.50 score 16 scripts 10 dependents

trevorhastie

softImpute:Matrix Completion via Iterative Soft-Thresholded SVD

Iterative methods for matrix completion that use nuclear-norm regularization. There are two main approaches.The one approach uses iterative soft-thresholded svds to impute the missing values. The second approach uses alternating least squares. Both have an 'EM' flavor, in that at each iteration the matrix is completed with the current estimate. For large matrices there is a special sparse-matrix class named "Incomplete" that efficiently handles all computations. The package includes procedures for centering and scaling rows, columns or both, and for computing low-rank SVDs on large sparse centered matrices (i.e. principal components).

Maintained by Trevor Hastie. Last updated 4 years ago.

fortran

10 stars 7.47 score 253 scripts 22 dependents

jiscah

sequoia:Pedigree Inference from SNPs

Multi-generational pedigree inference from incomplete data on hundreds of SNPs, including parentage assignment and sibship clustering. See Huisman (2017) (<DOI:10.1111/1755-0998.12665>) for more information.

Maintained by Jisca Huisman. Last updated 10 months ago.

pedigreepedigree-reconstructionpedigreessequoiasnpsnp-datafortran

26 stars 7.40 score 79 scripts

k-m-m

minpack.lm:R Interface to the Levenberg-Marquardt Nonlinear Least-Squares Algorithm Found in MINPACK, Plus Support for Bounds

The nls.lm function provides an R interface to lmder and lmdif from the MINPACK library, for solving nonlinear least-squares problems by a modification of the Levenberg-Marquardt algorithm, with support for lower and upper parameter bounds. The implementation can be used via nls-like calls using the nlsLM function.

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

fortranopenblas

1 stars 7.36 score 1.7k scripts 180 dependents

nlmixr2

lbfgsb3c:Limited Memory BFGS Minimizer with Bounds on Parameters with optim() 'C' Interface

Interfacing to Nocedal et al. L-BFGS-B.3.0 (See <http://users.iems.northwestern.edu/~nocedal/lbfgsb.html>) limited memory BFGS minimizer with bounds on parameters. This is a fork of 'lbfgsb3'. This registers a 'R' compatible 'C' interface to L-BFGS-B.3.0 that uses the same function types and optimization as the optim() function (see writing 'R' extensions and source for details). This package also adds more stopping criteria as well as allowing the adjustment of more tolerances.

Maintained by Matthew L Fidler. Last updated 6 months ago.

fortrancpp

1 stars 7.33 score 17 scripts 16 dependents

cran

PMCMRplus:Calculate Pairwise Multiple Comparisons of Mean Rank Sums Extended

For one-way layout experiments the one-way ANOVA can be performed as an omnibus test. All-pairs multiple comparisons tests (Tukey-Kramer test, Scheffe test, LSD-test) and many-to-one tests (Dunnett test) for normally distributed residuals and equal within variance are available. Furthermore, all-pairs tests (Games-Howell test, Tamhane's T2 test, Dunnett T3 test, Ury-Wiggins-Hochberg test) and many-to-one (Tamhane-Dunnett Test) for normally distributed residuals and heterogeneous variances are provided. Van der Waerden's normal scores test for omnibus, all-pairs and many-to-one tests is provided for non-normally distributed residuals and homogeneous variances. The Kruskal-Wallis, BWS and Anderson-Darling omnibus test and all-pairs tests (Nemenyi test, Dunn test, Conover test, Dwass-Steele-Critchlow- Fligner test) as well as many-to-one (Nemenyi test, Dunn test, U-test) are given for the analysis of variance by ranks. Non-parametric trend tests (Jonckheere test, Cuzick test, Johnson-Mehrotra test, Spearman test) are included. In addition, a Friedman-test for one-way ANOVA with repeated measures on ranks (CRBD) and Skillings-Mack test for unbalanced CRBD is provided with consequent all-pairs tests (Nemenyi test, Siegel test, Miller test, Conover test, Exact test) and many-to-one tests (Nemenyi test, Demsar test, Exact test). A trend can be tested with Pages's test. Durbin's test for a two-way balanced incomplete block design (BIBD) is given in this package as well as Gore's test for CRBD with multiple observations per cell is given. Outlier tests, Mandel's k- and h statistic as well as functions for Type I error and Power analysis as well as generic summary, print and plot methods are provided.

Maintained by Thorsten Pohlert. Last updated 7 months ago.

fortran

6 stars 7.24 score 12 dependents

k-m-m

nnls:The Lawson-Hanson Algorithm for Non-Negative Least Squares (NNLS)

An R interface to the Lawson-Hanson implementation of an algorithm for non-negative least squares (NNLS). Also allows the combination of non-negative and non-positive constraints.

Maintained by Katharine Mullen. Last updated 5 months ago.

fortran

7.18 score 251 scripts 166 dependents

fzao

caRamel:Automatic Calibration by Evolutionary Multi Objective Algorithm

The caRamel optimizer has been developed to meet the requirement for an automatic calibration procedure that delivers a family of parameter sets that are optimal with regard to a multi-objective target (Monteil et al. <doi:10.5194/hess-24-3189-2020>).

Maintained by Fabrice Zaoui. Last updated 8 months ago.

fortran

12 stars 7.01 score 41 scripts

psoerensen

qgg:Statistical Tools for Quantitative Genetic Analyses

Provides an infrastructure for efficient processing of large-scale genetic and phenotypic data including core functions for: 1) fitting linear mixed models, 2) constructing marker-based genomic relationship matrices, 3) estimating genetic parameters (heritability and correlation), 4) performing genomic prediction and genetic risk profiling, and 5) single or multi-marker association analyses. Rohde et al. (2019) <doi:10.1101/503631>.

Maintained by Peter Soerensen. Last updated 11 days ago.

fortranopenblascpp

36 stars 7.01 score 47 scripts

doccstat

fastcpd:Fast Change Point Detection via Sequential Gradient Descent

Implements fast change point detection algorithm based on the paper "Sequential Gradient Descent and Quasi-Newton's Method for Change-Point Analysis" by Xianyang Zhang, Trisha Dawn <https://proceedings.mlr.press/v206/zhang23b.html>. The algorithm is based on dynamic programming with pruning and sequential gradient descent. It is able to detect change points a magnitude faster than the vanilla Pruned Exact Linear Time(PELT). The package includes examples of linear regression, logistic regression, Poisson regression, penalized linear regression data, and whole lot more examples with custom cost function in case the user wants to use their own cost function.

Maintained by Xingchi Li. Last updated 12 days ago.

change-point-detectioncppcustom-functiongradient-descentlassolinear-regressionlogistic-regressionofflinepeltpenalized-regressionpoisson-regressionquasi-newtonstatisticstime-serieswarm-startfortranopenblascppopenmp

22 stars 7.00 score 7 scripts

adrian-bowman

sm:Smoothing Methods for Nonparametric Regression and Density Estimation

This is software linked to the book 'Applied Smoothing Techniques for Data Analysis - The Kernel Approach with S-Plus Illustrations' Oxford University Press.

Maintained by Adrian Bowman. Last updated 1 years ago.

fortran

1 stars 6.99 score 732 scripts 36 dependents

dajmcdon

sparsegl:Sparse Group Lasso

Efficient implementation of sparse group lasso with optional bound constraints on the coefficients; see <doi:10.18637/jss.v110.i06>. It supports the use of a sparse design matrix as well as returning coefficient estimates in a sparse matrix. Furthermore, it correctly calculates the degrees of freedom to allow for information criteria rather than cross-validation with very large data. Finally, the interface to compiled code avoids unnecessary copies and allows for the use of long integers.

Maintained by Daniel J. McDonald. Last updated 7 months ago.

fortran

18 stars 6.95 score 22 scripts 1 dependents

cran

mnormt:The Multivariate Normal and t Distributions, and Their Truncated Versions

Functions are provided for computing the density and the distribution function of d-dimensional normal and "t" random variables, possibly truncated (on one side or two sides), and for generating random vectors sampled from these distributions, except sampling from the truncated "t". Moments of arbitrary order of a multivariate truncated normal are computed, and converted to cumulants up to order 4. Probabilities are computed via non-Monte Carlo methods; different routines are used in the case d=1, d=2, d=3, d>3, if d denotes the dimensionality.

Maintained by Adelchi Azzalini. Last updated 3 years ago.

fortran

6.93 score 684 dependents

iagogv3

clusterCrit:Clustering Indices

Package providing functions for computing a collection of clustering validation or quality criteria and partition comparison indices.

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

fortranopenblas

6.81 score 213 scripts 5 dependents

angusian

Kendall:Kendall Rank Correlation and Mann-Kendall Trend Test

Computes the Kendall rank correlation and Mann-Kendall trend test. See documentation for use of block bootstrap when there is autocorrelation.

Maintained by A.I. McLeod. Last updated 3 years ago.

fortran

6.74 score 864 scripts 25 dependents

zhuwang46

mpath:Regularized Linear Models

Algorithms compute robust estimators for loss functions in the concave convex (CC) family by the iteratively reweighted convex optimization (IRCO), an extension of the iteratively reweighted least squares (IRLS). The IRCO reduces the weight of the observation that leads to a large loss; it also provides weights to help identify outliers. Applications include robust (penalized) generalized linear models and robust support vector machines. The package also contains penalized Poisson, negative binomial, zero-inflated Poisson, zero-inflated negative binomial regression models and robust models with non-convex loss functions. Wang et al. (2014) <doi:10.1002/sim.6314>, Wang et al. (2015) <doi:10.1002/bimj.201400143>, Wang et al. (2016) <doi:10.1177/0962280214530608>, Wang (2021) <doi:10.1007/s11749-021-00770-2>, Wang (2020) <arXiv:2010.02848>.

Maintained by Zhu Wang. Last updated 3 years ago.

fortranopenblas

1 stars 6.67 score 131 scripts 4 dependents

couthcommander

nbpMatching:Functions for Optimal Non-Bipartite Matching

Perform non-bipartite matching and matched randomization. A "bipartite" matching utilizes two separate groups, e.g. smokers being matched to nonsmokers or cases being matched to controls. A "non-bipartite" matching creates mates from one big group, e.g. 100 hospitals being randomized for a two-arm cluster randomized trial or 5000 children who have been exposed to various levels of secondhand smoke and are being paired to form a greater exposure vs. lesser exposure comparison. At the core of a non-bipartite matching is a N x N distance matrix for N potential mates. The distance between two units expresses a measure of similarity or quality as mates (the lower the better). The 'gendistance()' and 'distancematrix()' functions assist in creating this. The 'nonbimatch()' function creates the matching that minimizes the total sum of distances between mates; hence, it is referred to as an "optimal" matching. The 'assign.grp()' function aids in performing a matched randomization. Note bipartite matching can be performed using the prevent option in 'gendistance()'.

Maintained by Cole Beck. Last updated 6 months ago.

fortran

9 stars 6.66 score 85 scripts 5 dependents

r-forge

fUnitRoots:Rmetrics - Modelling Trends and Unit Roots

Provides four addons for analyzing trends and unit roots in financial time series: (i) functions for the density and probability of the augmented Dickey-Fuller Test, (ii) functions for the density and probability of MacKinnon's unit root test statistics, (iii) reimplementations for the ADF and MacKinnon Test, and (iv) an 'urca' Unit Root Test Interface for Pfaff's unit root test suite.

Maintained by Georgi N. Boshnakov. Last updated 10 days ago.

fortran

1 stars 6.64 score 292 scripts

elaliberte

FD:Measuring Functional Diversity (FD) from Multiple Traits, and Other Tools for Functional Ecology

Computes different multidimensional FD indices. Implements a distance-based framework to measure FD that allows any number and type of functional traits, and can also consider species relative abundances. Also contains other useful tools for functional ecology.

Maintained by Etienne Laliberté. Last updated 1 years ago.

fortran

4 stars 6.54 score 586 scripts 15 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

7 stars 6.52 score 12 scripts 10 dependents

faosorios

L1pack:Routines for L1 Estimation

L1 estimation for linear regression using Barrodale and Roberts' method <doi:10.1145/355616.361024> and the EM algorithm <doi:10.1023/A:1020759012226>. Estimation of mean and covariance matrix using the multivariate Laplace distribution, density, distribution function, quantile function and random number generation for univariate and multivariate Laplace distribution <doi:10.1080/03610929808832115>. Implementation of Naik and Plungpongpun <doi:10.1007/0-8176-4487-3_7> for the Generalized spatial median estimator is included.

Maintained by Felipe Osorio. Last updated 10 days ago.

fortran

6 stars 6.50 score 396 scripts 4 dependents

lauravana

mvord:Multivariate Ordinal Regression Models

A flexible framework for fitting multivariate ordinal regression models with composite likelihood methods. Methodological details are given in Hirk, Hornik, Vana (2020) <doi:10.18637/jss.v093.i04>.

Maintained by Laura Vana. Last updated 7 months ago.

fortran

4 stars 6.49 score 32 scripts

cran

nleqslv:Solve Systems of Nonlinear Equations

Solve a system of nonlinear equations using a Broyden or a Newton method with a choice of global strategies such as line search and trust region. There are options for using a numerical or user supplied Jacobian, for specifying a banded numerical Jacobian and for allowing a singular or ill-conditioned Jacobian.

Maintained by Berend Hasselman. Last updated 1 years ago.

fortranopenblas

3 stars 6.45 score 168 dependents

tslumley

biglm:Bounded Memory Linear and Generalized Linear Models

Regression for data too large to fit in memory.

Maintained by Thomas Lumley. Last updated 10 months ago.

fortran

1 stars 6.43 score 446 scripts 32 dependents

bioc

SynExtend:Tools for Working With Synteny Objects

Shared order between genomic sequences provide a great deal of information. Synteny objects produced by the R package DECIPHER provides quantitative information about that shared order. SynExtend provides tools for extracting information from Synteny objects.

Maintained by Nicholas Cooley. Last updated 16 days ago.

geneticsclusteringcomparativegenomicsdataimportfortranopenmp

1 stars 6.42 score 77 scripts

cran

gss:General Smoothing Splines

A comprehensive package for structural multivariate function estimation using smoothing splines.

Maintained by Chong Gu. Last updated 6 months ago.

fortranopenblas

3 stars 6.40 score 137 dependents

paobranco

UBL:An Implementation of Re-Sampling Approaches to Utility-Based Learning for Both Classification and Regression Tasks

Provides a set of functions that can be used to obtain better predictive performance on cost-sensitive and cost/benefits tasks (for both regression and classification). This includes re-sampling approaches that modify the original data set biasing it towards the user preferences.

Maintained by Paula Branco. Last updated 4 months ago.

fortran

33 stars 6.39 score 165 scripts 1 dependents

pmair78

eRm:Extended Rasch Modeling

Fits Rasch models (RM), linear logistic test models (LLTM), rating scale model (RSM), linear rating scale models (LRSM), partial credit models (PCM), and linear partial credit models (LPCM). Missing values are allowed in the data matrix. Additional features are the ML estimation of the person parameters, Andersen's LR-test, item-specific Wald test, Martin-Loef-Test, nonparametric Monte-Carlo Tests, itemfit and personfit statistics including infit and outfit measures, ICC and other plots, automated stepwise item elimination, simulation module for various binary data matrices.

Maintained by Patrick Mair. Last updated 4 days ago.

fortran

4 stars 6.38 score 182 scripts 5 dependents

pschmidtwalter

LWFBrook90R:Simulate Evapotranspiration and Soil Moisture with the SVAT Model LWF-Brook90

Provides a flexible and easy-to use interface for the soil vegetation atmosphere transport (SVAT) model LWF-BROOK90, written in Fortran. The model simulates daily transpiration, interception, soil and snow evaporation, streamflow and soil water fluxes through a soil profile covered with vegetation, as described in Hammel & Kennel (2001, ISBN:978-3-933506-16-0) and Federer et al. (2003) <doi:10.1175/1525-7541(2003)004%3C1276:SOAETS%3E2.0.CO;2>. A set of high-level functions for model set up, execution and parallelization provides easy access to plot-level SVAT simulations, as well as multi-run and large-scale applications.

Maintained by Paul Schmidt-Walter. Last updated 5 months ago.

evapotranspirationmodelingwaterbalancewaterfluxfortran

11 stars 6.38 score 27 scripts

faosorios

fastmatrix:Fast Computation of some Matrices Useful in Statistics

Small set of functions to fast computation of some matrices and operations useful in statistics and econometrics. Currently, there are functions for efficient computation of duplication, commutation and symmetrizer matrices with minimal storage requirements. Some commonly used matrix decompositions (LU and LDL), basic matrix operations (for instance, Hadamard, Kronecker products and the Sherman-Morrison formula) and iterative solvers for linear systems are also available. In addition, the package includes a number of common statistical procedures such as the sweep operator, weighted mean and covariance matrix using an online algorithm, linear regression (using Cholesky, QR, SVD, sweep operator and conjugate gradients methods), ridge regression (with optimal selection of the ridge parameter considering several procedures), omnibus tests for univariate normality, functions to compute the multivariate skewness, kurtosis, the Mahalanobis distance (checking the positive defineteness), and the Wilson-Hilferty transformation of gamma variables. Furthermore, the package provides interfaces to C code callable by another C code from other R packages.

Maintained by Felipe Osorio. Last updated 1 years ago.

commutation-matrixjarque-bera-testldl-factorizationlu-factorizationmatrix-api-for-r-packagesmatrix-normsmodified-choleskyols-regressionpower-methodridge-regressionsherman-morrisonstatisticssweep-operatorsymmetrizer-matrixfortranopenblas

19 stars 6.37 score 37 scripts 11 dependents

dwinsemius

muhaz:Hazard Function Estimation in Survival Analysis

Produces a smooth estimate of the hazard function for censored data.

Maintained by David Winsemius. Last updated 4 years ago.

fortran

6.37 score 180 scripts 51 dependents

cran

fGarch:Rmetrics - Autoregressive Conditional Heteroskedastic Modelling

Analyze and model heteroskedastic behavior in financial time series.

Maintained by Georgi N. Boshnakov. Last updated 1 years ago.

fortran

7 stars 6.33 score 51 dependents

jorischau

gslnls:GSL Multi-Start Nonlinear Least-Squares Fitting

An R interface to weighted nonlinear least-squares optimization with the GNU Scientific Library (GSL), see M. Galassi et al. (2009, ISBN:0954612078). The available trust region methods include the Levenberg-Marquardt algorithm with and without geodesic acceleration, the Steihaug-Toint conjugate gradient algorithm for large systems and several variants of Powell's dogleg algorithm. Multi-start optimization based on quasi-random samples is implemented using a modified version of the algorithm in Hickernell and Yuan (1997, OR Transactions). Robust nonlinear regression can be performed using various robust loss functions, in which case the optimization problem is solved by iterative reweighted least squares (IRLS). Bindings are provided to tune a number of parameters affecting the low-level aspects of the trust region algorithms. The interface mimics R's nls() function and returns model objects inheriting from the same class.

Maintained by Joris Chau. Last updated 2 months ago.

gnu-scientific-librarygsllevenberg-marquardtmulti-startnonlinear-least-squaresnonlinear-regressionrobust-regresssionfortranglibc

16 stars 6.23 score 35 scripts 2 dependents

cran

glasso:Graphical Lasso: Estimation of Gaussian Graphical Models

Estimation of a sparse inverse covariance matrix using a lasso (L1) penalty. Facilities are provided for estimates along a path of values for the regularization parameter.

Maintained by Rob Tibshirani. Last updated 5 years ago.

fortran

2 stars 6.09 score 109 dependents

goranbrostrom

glmmML:Generalized Linear Models with Clustering

Binomial and Poisson regression for clustered data, fixed and random effects with bootstrapping.

Maintained by Göran Broström. Last updated 6 months ago.

fortranopenblas

6.09 score 215 scripts 5 dependents

cran

cmprsk:Subdistribution Analysis of Competing Risks

Estimation, testing and regression modeling of subdistribution functions in competing risks, as described in Gray (1988), A class of K-sample tests for comparing the cumulative incidence of a competing risk, Ann. Stat. 16:1141-1154 <DOI:10.1214/aos/1176350951>, and Fine JP and Gray RJ (1999), A proportional hazards model for the subdistribution of a competing risk, JASA, 94:496-509, <DOI:10.1080/01621459.1999.10474144>.

Maintained by Bob Gray. Last updated 10 months ago.

fortran

3 stars 6.07 score 65 dependents

dvrbts

labdsv:Ordination and Multivariate Analysis for Ecology

A variety of ordination and community analyses useful in analysis of data sets in community ecology. Includes many of the common ordination methods, with graphical routines to facilitate their interpretation, as well as several novel analyses.

Maintained by David W. Roberts. Last updated 2 years ago.

fortran

3 stars 6.05 score 452 scripts 12 dependents

jclavel

glassoFast:Fast Graphical LASSO

A fast and improved implementation of the graphical LASSO.

Maintained by Julien Clavel. Last updated 7 years ago.

fortran

5 stars 6.04 score 69 scripts 17 dependents

john-d-fox

norm:Analysis of Multivariate Normal Datasets with Missing Values

An integrated set of functions for the analysis of multivariate normal datasets with missing values, including implementation of the EM algorithm, data augmentation, and multiple imputation.

Maintained by John Fox. Last updated 2 years ago.

fortran

5.99 score 106 scripts 33 dependents

cran

dotCall64:Enhanced Foreign Function Interface Supporting Long Vectors

Provides .C64(), which is an enhanced version of .C() and .Fortran() from the foreign function interface. .C64() supports long vectors, arguments of type 64-bit integer, and provides a mechanism to avoid unnecessary copies of read-only and write-only arguments. This makes it a convenient and fast interface to C/C++ and Fortran code.

Maintained by Reinhard Furrer. Last updated 6 months ago.

fortranopenmp

5.90 score 439 dependents

faosorios

SpatialPack:Tools for Assessment the Association Between Two Spatial Processes

Tools to assess the association between two spatial processes. Currently, several methodologies are implemented: A modified t-test to perform hypothesis testing about the independence between the processes, a suitable nonparametric correlation coefficient, the codispersion coefficient, and an F test for assessing the multiple correlation between one spatial process and several others. Functions for image processing and computing the spatial association between images are also provided. Functions contained in the package are intended to accompany Vallejos, R., Osorio, F., Bevilacqua, M. (2020). Spatial Relationships Between Two Georeferenced Variables: With Applications in R. Springer, Cham <doi:10.1007/978-3-030-56681-4>.

Maintained by Felipe Osorio. Last updated 9 days ago.

codispersion-coefficientmodified-t-testspatial-associationspatial-processesssimstructural-similaritytjostheim-coefficientfortran

7 stars 5.88 score 73 scripts 1 dependents

toshi-ara

brunnermunzel:(Permuted) Brunner-Munzel Test

Provides the functions for Brunner-Munzel test and permuted Brunner-Munzel test, which enable to use formula, matrix, and table as argument. These functions are based on Brunner and Munzel (2000) <doi:10.1002/(SICI)1521-4036(200001)42:1%3C17::AID-BIMJ17%3E3.0.CO;2-U> and Neubert and Brunner (2007) <doi:10.1016/j.csda.2006.05.024>, and are written with FORTRAN.

Maintained by Toshiaki Ara. Last updated 3 years ago.

fortran

5 stars 5.83 score 30 scripts 1 dependents

trotsiuk

r3PG:Simulating Forest Growth using the 3-PG Model

Provides a flexible and easy-to-use interface for the Physiological Processes Predicting Growth (3-PG) model written in Fortran. The r3PG serves as a flexible and easy-to-use interface for the 3-PGpjs (monospecific, evenaged and evergreen forests) described in Landsberg & Waring (1997) <doi:10.1016/S0378-1127(97)00026-1> and the 3-PGmix (deciduous, uneven-aged or mixed-species forests) described in Forrester & Tang (2016) <doi:10.1016/j.ecolmodel.2015.07.010>.

Maintained by Volodymyr Trotsiuk. Last updated 10 months ago.

fortranglibc

27 stars 5.83 score 25 scripts

bioc

iClusterPlus:Integrative clustering of multi-type genomic data

Integrative clustering of multiple genomic data using a joint latent variable model.

Maintained by Qianxing Mo. Last updated 4 months ago.

multi-omicsclusteringfortranopenblas

5.76 score 190 scripts

r-forge

DPQ:Density, Probability, Quantile ('DPQ') Computations

Computations for approximations and alternatives for the 'DPQ' (Density (pdf), Probability (cdf) and Quantile) functions for probability distributions in R. Primary focus is on (central and non-central) beta, gamma and related distributions such as the chi-squared, F, and t. -- For several distribution functions, provide functions implementing formulas from Johnson, Kotz, and Kemp (1992) <doi:10.1002/bimj.4710360207> and Johnson, Kotz, and Balakrishnan (1995) for discrete or continuous distributions respectively. This is for the use of researchers in these numerical approximation implementations, notably for my own use in order to improve standard R pbeta(), qgamma(), ..., etc: {'"dpq"'-functions}.

Maintained by Martin Maechler. Last updated 2 months ago.

fortran

5.75 score 43 scripts 1 dependents

sestelo

npregfast:Nonparametric Estimation of Regression Models with Factor-by-Curve Interactions

A method for obtaining nonparametric estimates of regression models with or without factor-by-curve interactions using local polynomial kernel smoothers or splines. Additionally, a parametric model (allometric model) can be estimated.

Maintained by Marta Sestelo. Last updated 3 months ago.

allometricbarnaclecritical-pointscurve-interactionsfactor-by-curvefortraninteractionnonparametricregression-modelstesting

5 stars 5.73 score 89 scripts 2 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

7 stars 5.71 score 40 dependents

rubenfcasal

npsp:Nonparametric Spatial Statistics

Multidimensional nonparametric spatial (spatio-temporal) geostatistics. S3 classes and methods for multidimensional: linear binning, local polynomial kernel regression (spatial trend estimation), density and variogram estimation. Nonparametric methods for simultaneous inference on both spatial trend and variogram functions (for spatial processes). Nonparametric residual kriging (spatial prediction). For details on these methods see, for example, Fernandez-Casal and Francisco-Fernandez (2014) <doi:10.1007/s00477-013-0817-8> or Castillo-Paez et al. (2019) <doi:10.1016/j.csda.2019.01.017>.

Maintained by Ruben Fernandez-Casal. Last updated 5 months ago.

geostatisticsspatial-data-analysisstatisticsfortranopenblas

4 stars 5.71 score 64 scripts

cran

pspline:Penalized Smoothing Splines

Smoothing splines with penalties on order m derivatives.

Maintained by Brian Ripley. Last updated 4 months ago.

fortran

1 stars 5.69 score 94 dependents

cran

polspline:Polynomial Spline Routines

Routines for the polynomial spline fitting routines hazard regression, hazard estimation with flexible tails, logspline, lspec, polyclass, and polymars, by C. Kooperberg and co-authors.

Maintained by Charles Kooperberg. Last updated 11 months ago.

fortranopenblas

5.65 score 131 dependents

georgheinze

coxphf:Cox Regression with Firth's Penalized Likelihood

Implements Firth's penalized maximum likelihood bias reduction method for Cox regression which has been shown to provide a solution in case of monotone likelihood (nonconvergence of likelihood function), see Heinze and Schemper (2001) and Heinze and Dunkler (2008). The program fits profile penalized likelihood confidence intervals which were proved to outperform Wald confidence intervals.

Maintained by Georg Heinze. Last updated 2 years ago.

fortran

2 stars 5.63 score 36 scripts 1 dependents

cran

lmom:L-Moments

Functions related to L-moments: computation of L-moments and trimmed L-moments of distributions and data samples; parameter estimation; L-moment ratio diagram; plot vs. quantiles of an extreme-value distribution.

Maintained by J. R. M. Hosking. Last updated 6 months ago.

fortran

2 stars 5.63 score 140 dependents

kharchenkolab

leidenAlg:Implements the Leiden Algorithm via an R Interface

An R interface to the Leiden algorithm, an iterative community detection algorithm on networks. The algorithm is designed to converge to a partition in which all subsets of all communities are locally optimally assigned, yielding communities guaranteed to be connected. The implementation proves to be fast, scales well, and can be run on graphs of millions of nodes (as long as they can fit in memory). The original implementation was constructed as a python interface "leidenalg" found here: <https://github.com/vtraag/leidenalg>. The algorithm was originally described in Traag, V.A., Waltman, L. & van Eck, N.J. "From Louvain to Leiden: guaranteeing well-connected communities". Sci Rep 9, 5233 (2019) <doi:10.1038/s41598-019-41695-z>.

Maintained by Evan Biederstedt. Last updated 5 months ago.

fortrancpp

9 stars 5.61 score 28 scripts 5 dependents

cran

frailtypack:Shared, Joint (Generalized) Frailty Models; Surrogate Endpoints

The following several classes of frailty models using a penalized likelihood estimation on the hazard function but also a parametric estimation can be fit using this R package: 1) A shared frailty model (with gamma or log-normal frailty distribution) and Cox proportional hazard model. Clustered and recurrent survival times can be studied. 2) Additive frailty models for proportional hazard models with two correlated random effects (intercept random effect with random slope). 3) Nested frailty models for hierarchically clustered data (with 2 levels of clustering) by including two iid gamma random effects. 4) Joint frailty models in the context of the joint modelling for recurrent events with terminal event for clustered data or not. A joint frailty model for two semi-competing risks and clustered data is also proposed. 5) Joint general frailty models in the context of the joint modelling for recurrent events with terminal event data with two independent frailty terms. 6) Joint Nested frailty models in the context of the joint modelling for recurrent events with terminal event, for hierarchically clustered data (with two levels of clustering) by including two iid gamma random effects. 7) Multivariate joint frailty models for two types of recurrent events and a terminal event. 8) Joint models for longitudinal data and a terminal event. 9) Trivariate joint models for longitudinal data, recurrent events and a terminal event. 10) Joint frailty models for the validation of surrogate endpoints in multiple randomized clinical trials with failure-time and/or longitudinal endpoints with the possibility to use a mediation analysis model. 11) Conditional and Marginal two-part joint models for longitudinal semicontinuous data and a terminal event. 12) Joint frailty-copula models for the validation of surrogate endpoints in multiple randomized clinical trials with failure-time endpoints. 13) Generalized shared and joint frailty models for recurrent and terminal events. Proportional hazards (PH), additive hazard (AH), proportional odds (PO) and probit models are available in a fully parametric framework. For PH and AH models, it is possible to consider type-varying coefficients and flexible semiparametric hazard function. Prediction values are available (for a terminal event or for a new recurrent event). Left-truncated (not for Joint model), right-censored data, interval-censored data (only for Cox proportional hazard and shared frailty model) and strata are allowed. In each model, the random effects have the gamma or normal distribution. Now, you can also consider time-varying covariates effects in Cox, shared and joint frailty models (1-5). The package includes concordance measures for Cox proportional hazards models and for shared frailty models. 14) Competing Joint Frailty Model: A single type of recurrent event and two terminal events. 15) functions to compute power and sample size for four Gamma-frailty-based designs: Shared Frailty Models, Nested Frailty Models, Joint Frailty Models, and General Joint Frailty Models. Each design includes two primary functions: a power function, which computes power given a specified sample size; and a sample size function, which computes the required sample size to achieve a specified power. Moreover, the package can be used with its shiny application, in a local mode or by following the link below.

Maintained by Virginie Rondeau. Last updated 23 days ago.

fortranopenmp

7 stars 5.56 score 1 dependents

r-forge

lokern:Kernel Regression Smoothing with Local or Global Plug-in Bandwidth

Kernel regression smoothing with adaptive local or global plug-in bandwidth selection.

Maintained by Martin Maechler. Last updated 3 months ago.

fortran

5.53 score 64 scripts 5 dependents

cran

gee:Generalized Estimation Equation Solver

Generalized Estimation Equation solver.

Maintained by Brian Ripley. Last updated 4 months ago.

fortranopenblas

3 stars 5.50 score 18 dependents

kangy10

DRIP:Discontinuous Regression and Image Processing

A collection of functions that perform jump regression and image analysis such as denoising, deblurring and jump detection. The implemented methods are based on the following research: Qiu, P. (1998) <doi:10.1214/aos/1024691468>, Qiu, P. and Yandell, B. (1997) <doi: 10.1080/10618600.1997.10474746>, Qiu, P. (2009) <doi: 10.1007/s10463-007-0166-9>, Kang, Y. and Qiu, P. (2014) <doi: 10.1080/00401706.2013.844732>, Qiu, P. and Kang, Y. (2015) <doi: 10.5705/ss.2014.054>, Kang, Y., Mukherjee, P.S. and Qiu, P. (2018) <doi: 10.1080/00401706.2017.1415975>, Kang, Y. (2020) <doi: 10.1080/10618600.2019.1665536>.

Maintained by Yicheng Kang. Last updated 4 months ago.

fortranopenblas

5.49 score 31 scripts

biometrician

coxphw:Weighted Estimation in Cox Regression

Implements weighted estimation in Cox regression as proposed by Schemper, Wakounig and Heinze (Statistics in Medicine, 2009, <doi:10.1002/sim.3623>) and as described in Dunkler, Ploner, Schemper and Heinze (Journal of Statistical Software, 2018, <doi:10.18637/jss.v084.i02>). Weighted Cox regression provides unbiased average hazard ratio estimates also in case of non-proportional hazards. Approximated generalized concordance probability an effect size measure for clear-cut decisions can be obtained. The package provides options to estimate time-dependent effects conveniently by including interactions of covariates with arbitrary functions of time, with or without making use of the weighting option.

Maintained by Daniela Dunkler. Last updated 1 years ago.

cox-regressionsurvival-analysisfortran

1 stars 5.45 score 27 scripts 1 dependents

danielmork

dlmtree:Bayesian Treed Distributed Lag Models

Estimation of distributed lag models (DLMs) based on a Bayesian additive regression trees framework. Includes several extensions of DLMs: treed DLMs and distributed lag mixture models (Mork and Wilson, 2023) <doi:10.1111/biom.13568>; treed distributed lag nonlinear models (Mork and Wilson, 2022) <doi:10.1093/biostatistics/kxaa051>; heterogeneous DLMs (Mork, et. al., 2024) <doi:10.1080/01621459.2023.2258595>; monotone DLMs (Mork and Wilson, 2024) <doi:10.1214/23-BA1412>. The package also includes visualization tools and a 'shiny' interface to help interpret results.

Maintained by Daniel Mork. Last updated 2 months ago.

fortrancppopenmp

21 stars 5.40 score 17 scripts

cran

airGR:Suite of GR Hydrological Models for Precipitation-Runoff Modelling

Hydrological modelling tools developed at INRAE-Antony (HYCAR Research Unit, France). The package includes several conceptual rainfall-runoff models (GR4H, GR5H, GR4J, GR5J, GR6J, GR2M, GR1A) that can be applied either on a lumped or semi-distributed way. A snow accumulation and melt model (CemaNeige) and the associated functions for the calibration and evaluation of models are also included. Use help(airGR) for package description and references.

Maintained by Olivier Delaigue. Last updated 1 years ago.

fortran

4 stars 5.39 score 4 dependents

jqveenstra

arfima:Fractional ARIMA (and Other Long Memory) Time Series Modeling

Simulates, fits, and predicts long-memory and anti-persistent time series, possibly mixed with ARMA, regression, transfer-function components. Exact methods (MLE, forecasting, simulation) are used.

Maintained by JQ Veenstra. Last updated 1 years ago.

fortranopenblas

14 stars 5.31 score 81 scripts 1 dependents

cran

trend:Non-Parametric Trend Tests and Change-Point Detection

The analysis of environmental data often requires the detection of trends and change-points. This package includes tests for trend detection (Cox-Stuart Trend Test, Mann-Kendall Trend Test, (correlated) Hirsch-Slack Test, partial Mann-Kendall Trend Test, multivariate (multisite) Mann-Kendall Trend Test, (Seasonal) Sen's slope, partial Pearson and Spearman correlation trend test), change-point detection (Lanzante's test procedures, Pettitt's test, Buishand Range Test, Buishand U Test, Standard Normal Homogeinity Test), detection of non-randomness (Wallis-Moore Phase Frequency Test, Bartels rank von Neumann's ratio test, Wald-Wolfowitz Test) and the two sample Robust Rank-Order Distributional Test.

Maintained by Thorsten Pohlert. Last updated 1 years ago.

fortran

3 stars 5.31 score 9 dependents

cran

ash:David Scott's ASH Routines

David Scott's ASH routines ported from S-PLUS to R.

Maintained by Albrecht Gebhardt. Last updated 10 years ago.

fortran

5.26 score 171 dependents

snoweye

QZ:Generalized Eigenvalues and QZ Decomposition

Generalized eigenvalues and eigenvectors use QZ decomposition (generalized Schur decomposition). The decomposition needs an N-by-N non-symmetric matrix A or paired matrices (A,B) with eigenvalues reordering mechanism. The decomposition functions are mainly based Fortran subroutines in complex*16 and double precision of LAPACK library (version 3.10.0 or later).

Maintained by Wei-Chen Chen. Last updated 2 years ago.

fortranopenblas

2 stars 5.20 score 53 scripts

sgsokol

rmumps:Wrapper for MUMPS Library

Some basic features of 'MUMPS' (Multifrontal Massively Parallel sparse direct Solver) are wrapped in a class whose methods can be used for sequentially solving a sparse linear system (symmetric or not) with one or many right hand sides (dense or sparse). There is a possibility to do separately symbolic analysis, LU (or LDL^t) factorization and system solving. Third part ordering libraries are included and can be used: 'PORD', 'METIS', 'SCOTCH'. 'MUMPS' method was first described in Amestoy et al. (2001) <doi:10.1137/S0895479899358194> and Amestoy et al. (2006) <doi:10.1016/j.parco.2005.07.004>.

Maintained by Serguei Sokol. Last updated 9 months ago.

fortranopenblascpp

10 stars 5.18 score 17 scripts 2 dependents

r-forge

lpridge:Local Polynomial (Ridge) Regression

Local Polynomial Regression with Ridging.

Maintained by Martin Maechler. Last updated 3 months ago.

fortran

5.10 score 8 scripts 2 dependents

spgarbet

acepack:ACE and AVAS for Selecting Multiple Regression Transformations

Two nonparametric methods for multiple regression transform selection are provided. The first, Alternating Conditional Expectations (ACE), is an algorithm to find the fixed point of maximal correlation, i.e. it finds a set of transformed response variables that maximizes R^2 using smoothing functions [see Breiman, L., and J.H. Friedman. 1985. "Estimating Optimal Transformations for Multiple Regression and Correlation". Journal of the American Statistical Association. 80:580-598. <doi:10.1080/01621459.1985.10478157>]. Also included is the Additivity Variance Stabilization (AVAS) method which works better than ACE when correlation is low [see Tibshirani, R. 1986. "Estimating Transformations for Regression via Additivity and Variance Stabilization". Journal of the American Statistical Association. 83:394-405. <doi:10.1080/01621459.1988.10478610>]. A good introduction to these two methods is in chapter 16 of Frank Harrell's "Regression Modeling Strategies" in the Springer Series in Statistics. A permutation independence test is included from [Holzmann, H., Klar, B. 2025. "Lancaster correlation - a new dependence measure linked to maximum correlation". Scandinavian Journal of Statistics. 52(1):145-169 <doi:10.1111/sjos.12733>].

Maintained by Shawn Garbett. Last updated 2 months ago.

fortran

5.08 score 50 scripts 3 dependents

bioc

NuPoP:An R package for nucleosome positioning prediction

NuPoP is an R package for Nucleosome Positioning Prediction.This package is built upon a duration hidden Markov model proposed in Xi et al, 2010; Wang et al, 2008. The core of the package was written in Fotran. In addition to the R package, a stand-alone Fortran software tool is also available at https://github.com/jipingw. The Fortran codes have complete functonality as the R package. Note: NuPoP has two separate functions for prediction of nucleosome positioning, one for MNase-map trained models and the other for chemical map-trained models. The latter was implemented for four species including yeast, S.pombe, mouse and human, trained based on our recent publications. We noticed there is another package nuCpos by another group for prediction of nucleosome positioning trained with chemicals. A report to compare recent versions of NuPoP with nuCpos can be found at https://github.com/jiping/NuPoP_doc. Some more information can be found and will be posted at https://github.com/jipingw/NuPoP.

Maintained by Ji-Ping Wang. Last updated 5 months ago.

geneticsvisualizationclassificationnucleosomepositioninghiddenmarkovmodelfortran

5.04 score 11 scripts

aadler

Delaporte:Statistical Functions for the Delaporte Distribution

Provides probability mass, distribution, quantile, random-variate generation, and method-of-moments parameter-estimation functions for the Delaporte distribution with parameterization based on Vose (2008) <isbn:9780470512845>. The Delaporte is a discrete probability distribution which can be considered the convolution of a negative binomial distribution with a Poisson distribution. Alternatively, it can be considered a counting distribution with both Poisson and negative binomial components. It has been studied in actuarial science as a frequency distribution which has more variability than the Poisson, but less than the negative binomial.

Maintained by Avraham Adler. Last updated 10 months ago.

fortranopenmp

4 stars 5.00 score 14 scripts 2 dependents

psegaert

mrfDepth:Depth Measures in Multivariate, Regression and Functional Settings

Tools to compute depth measures and implementations of related tasks such as outlier detection, data exploration and classification of multivariate, regression and functional data.

Maintained by Jakob Raymaekers. Last updated 6 years ago.

fortranopenblascpp

3 stars 4.99 score 72 scripts 3 dependents

tibshirani

samr:SAM: Significance Analysis of Microarrays

Significance Analysis of Microarrays for differential expression analysis, RNAseq data and related problems.

Maintained by Rob Tibshirani. Last updated 6 years ago.

fortran

3 stars 4.97 score 208 scripts 1 dependents

archer-yang-lab

gcdnet:The (Adaptive) LASSO and Elastic Net Penalized Least Squares, Logistic Regression, Hybrid Huberized Support Vector Machines, Squared Hinge Loss Support Vector Machines and Expectile Regression using a Fast Generalized Coordinate Descent Algorithm

Implements a generalized coordinate descent (GCD) algorithm for computing the solution paths of the hybrid Huberized support vector machine (HHSVM) and its generalizations. Supported models include the (adaptive) LASSO and elastic net penalized least squares, logistic regression, HHSVM, squared hinge loss SVM and expectile regression.

Maintained by Yi Yang. Last updated 3 years ago.

fortran

7 stars 4.91 score 64 scripts 2 dependents

r-forge

Gifi:Multivariate Analysis with Optimal Scaling

Implements categorical principal component analysis ('PRINCALS'), multiple correspondence analysis ('HOMALS'), monotone regression analysis ('MORALS'). It replaces the 'homals' package.

Maintained by Patrick Mair. Last updated 4 days ago.

fortran

4.90 score 37 scripts 1 dependents

ktabelow

qMRI:Methods for Quantitative Magnetic Resonance Imaging ('qMRI')

Implementation of methods for estimation of quantitative maps from Multi-Parameter Mapping (MPM) acquisitions (Weiskopf et al. (2013) <doi:10.3389/fnins.2013.00095>) and analysis of Inversion Recovery MRI data. Usage of the package is described in Polzehl and Tabelow (2023), "Magnetic Resonance Brain Imaging", 2nd Edition, Chapter 6 and 7, Springer, Use R! Series. <doi:10.1007/978-3-031-38949-8>. J. Polzehl and K. Tabelow (2023), "Magnetic Resonance Brain Imaging - Modeling and Data Analysis Using R: Code and Data." <doi:10.20347/WIAS.DATA.6> provides extensive example code and data.

Maintained by Karsten Tabelow. Last updated 23 days ago.

fortran

4.81 score 36 scripts

waleedalmutiry

EpiILM:Spatial and Network Based Individual Level Models for Epidemics

Provides tools for simulating from discrete-time individual level models for infectious disease data analysis. This epidemic model class contains spatial and contact-network based models with two disease types: Susceptible-Infectious (SI) and Susceptible-Infectious-Removed (SIR).

Maintained by Waleed Almutiry. Last updated 4 years ago.

fortran

6 stars 4.80 score 21 scripts

pchausse

momentfit:Methods of Moments

Several classes for moment-based models are defined. The classes are defined for moment conditions derived from a single equation or a system of equations. The conditions can also be expressed as functions or formulas. Several methods are also offered to facilitate the development of different estimation techniques. The methods that are currently provided are the Generalized method of moments (Hansen 1982; <doi:10.2307/1912775>), for single equations and systems of equation, and the Generalized Empirical Likelihood (Smith 1997; <doi:10.1111/j.0013-0133.1997.174.x>, Kitamura 1997; <doi:10.1214/aos/1069362388>, Newey and Smith 2004; <doi:10.1111/j.1468-0262.2004.00482.x>, and Anatolyev 2005 <doi:10.1111/j.1468-0262.2005.00601.x>).

Maintained by Pierre Chausse. Last updated 1 years ago.

fortranopenblas

4.80 score 21 scripts 1 dependents

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.

fortranglibc

4.76 score 116 scripts

swihart

event:Event History Procedures and Models

Functions for setting up and analyzing event history data.

Maintained by Bruce Swihart. Last updated 8 years ago.

fortran

1 stars 4.74 score 548 scripts

karlines

marelac:Tools for Aquatic Sciences

Datasets, constants, conversion factors, and utilities for 'MArine', 'Riverine', 'Estuarine', 'LAcustrine' and 'Coastal' science. The package contains among others: (1) chemical and physical constants and datasets, e.g. atomic weights, gas constants, the earths bathymetry; (2) conversion factors (e.g. gram to mol to liter, barometric units, temperature, salinity); (3) physical functions, e.g. to estimate concentrations of conservative substances, gas transfer and diffusion coefficients, the Coriolis force and gravity; (4) thermophysical properties of the seawater, as from the UNESCO polynomial or from the more recent derivation based on a Gibbs function.

Maintained by Karline Soetaert. Last updated 2 years ago.

fortran

4.63 score 119 scripts 4 dependents

jpolzehl

aws:Adaptive Weights Smoothing

We provide a collection of R-functions implementing adaptive smoothing procedures in 1D, 2D and 3D. This includes the Propagation-Separation Approach to adaptive smoothing, the Intersecting Confidence Intervals (ICI), variational approaches and a non-local means filter. The package is described in detail in Polzehl J, Papafitsoros K, Tabelow K (2020). Patch-Wise Adaptive Weights Smoothing in R. Journal of Statistical Software, 95(6), 1-27. <doi:10.18637/jss.v095.i06>, Usage of the package in MR imaging is illustrated in Polzehl and Tabelow (2023), Magnetic Resonance Brain Imaging, 2nd Ed. Appendix A, Springer, Use R! Series. <doi:10.1007/978-3-031-38949-8>.

Maintained by Joerg Polzehl. Last updated 6 months ago.

fortranopenblasopenmp

4.61 score 38 scripts 8 dependents

dsco036

DistributionUtils:Distribution Utilities

Utilities are provided which are of use in the packages I have developed for dealing with distributions. Currently these packages are GeneralizedHyperbolic, VarianceGamma, and SkewHyperbolic and NormalLaplace. Each of these packages requires DistributionUtils. Functionality includes sample skewness and kurtosis, log-histogram, tail plots, moments by integration, changing the point about which a moment is calculated, functions for testing distributions using inversion tests and the Massart inequality. Also includes an implementation of the incomplete Bessel K function.

Maintained by David Scott. Last updated 20 hours ago.

fortran

4.61 score 32 scripts 32 dependents

francescobartolucci

LMest:Generalized Latent Markov Models

Latent Markov models for longitudinal continuous and categorical data. See Bartolucci, Pandolfi, Pennoni (2017)<doi:10.18637/jss.v081.i04>.

Maintained by Francesco Bartolucci. Last updated 3 months ago.

fortranopenblas

3 stars 4.58 score 42 scripts

karlines

ReacTran:Reactive Transport Modelling in 1d, 2d and 3d

Routines for developing models that describe reaction and advective-diffusive transport in one, two or three dimensions. Includes transport routines in porous media, in estuaries, and in bodies with variable shape.

Maintained by Karline Soetaert. Last updated 8 years ago.

fortran

6 stars 4.57 score 52 scripts

cran

VCA:Variance Component Analysis

ANOVA and REML estimation of linear mixed models is implemented, once following Searle et al. (1991, ANOVA for unbalanced data), once making use of the 'lme4' package. The primary objective of this package is to perform a variance component analysis (VCA) according to CLSI EP05-A3 guideline "Evaluation of Precision of Quantitative Measurement Procedures" (2014). There are plotting methods for visualization of an experimental design, plotting random effects and residuals. For ANOVA type estimation two methods for computing ANOVA mean squares are implemented (SWEEP and quadratic forms). The covariance matrix of variance components can be derived, which is used in estimating confidence intervals. Linear hypotheses of fixed effects and LS means can be computed. LS means can be computed at specific values of covariables and with custom weighting schemes for factor variables. See ?VCA for a more comprehensive description of the features.

Maintained by Andre Schuetzenmeister. Last updated 1 years ago.

fortranopenblas

2 stars 4.51 score 5 dependents

cran

akima:Interpolation of Irregularly and Regularly Spaced Data

Several cubic spline interpolation methods of H. Akima for irregular and regular gridded data are available through this package, both for the bivariate case (irregular data: ACM 761, regular data: ACM 760) and univariate case (ACM 433 and ACM 697). Linear interpolation of irregular gridded data is also covered by reusing D. J. Renkas triangulation code which is part of Akimas Fortran code. A bilinear interpolator for regular grids was also added for comparison with the bicubic interpolator on regular grids.

Maintained by Albrecht Gebhardt. Last updated 3 years ago.

fortran

5 stars 4.48 score 2 dependents

cran

CSTools:Assessing Skill of Climate Forecasts on Seasonal-to-Decadal Timescales

Exploits dynamical seasonal forecasts in order to provide information relevant to stakeholders at the seasonal timescale. The package contains process-based methods for forecast calibration, bias correction, statistical and stochastic downscaling, optimal forecast combination and multivariate verification, as well as basic and advanced tools to obtain tailored products. This package was developed in the context of the 'ERA4CS' project 'MEDSCOPE' and the 'H2020 S2S4E' project and includes contributions from 'ArticXchange' project founded by 'EU-PolarNet 2'. 'Pérez-Zanón et al. (2022) <doi:10.5194/gmd-15-6115-2022>'. 'Doblas-Reyes et al. (2005) <doi:10.1111/j.1600-0870.2005.00104.x>'. 'Mishra et al. (2018) <doi:10.1007/s00382-018-4404-z>'. 'Sanchez-Garcia et al. (2019) <doi:10.5194/asr-16-165-2019>'. 'Straus et al. (2007) <doi:10.1175/JCLI4070.1>'. 'Terzago et al. (2018) <doi:10.5194/nhess-18-2825-2018>'. 'Torralba et al. (2017) <doi:10.1175/JAMC-D-16-0204.1>'. 'D'Onofrio et al. (2014) <doi:10.1175/JHM-D-13-096.1>'. 'Verfaillie et al. (2017) <doi:10.5194/gmd-10-4257-2017>'. 'Van Schaeybroeck et al. (2019) <doi:10.1016/B978-0-12-812372-0.00010-8>'. 'Yiou et al. (2013) <doi:10.1007/s00382-012-1626-3>'.

Maintained by Victoria Agudetse. Last updated 1 years ago.

fortran

2 stars 4.48 score 1 dependents

pokotylo

ddalpha:Depth-Based Classification and Calculation of Data Depth

Contains procedures for depth-based supervised learning, which are entirely non-parametric, in particular the DDalpha-procedure (Lange, Mosler and Mozharovskyi, 2014 <doi:10.1007/s00362-012-0488-4>). The training data sample is transformed by a statistical depth function to a compact low-dimensional space, where the final classification is done. It also offers an extension to functional data and routines for calculating certain notions of statistical depth functions. 50 multivariate and 5 functional classification problems are included. (Pokotylo, Mozharovskyi and Dyckerhoff, 2019 <doi:10.18637/jss.v091.i05>).

Maintained by Oleksii Pokotylo. Last updated 6 months ago.

fortrancpp

2 stars 4.45 score 211 scripts 7 dependents

jstriaukas

midasml:Estimation and Prediction Methods for High-Dimensional Mixed Frequency Time Series Data

The 'midasml' package implements estimation and prediction methods for high-dimensional mixed-frequency (MIDAS) time-series and panel data regression models. The regularized MIDAS models are estimated using orthogonal (e.g. Legendre) polynomials and sparse-group LASSO (sg-LASSO) estimator. For more information on the 'midasml' approach see Babii, Ghysels, and Striaukas (2021, JBES forthcoming) <doi:10.1080/07350015.2021.1899933>. The package is equipped with the fast implementation of the sg-LASSO estimator by means of proximal block coordinate descent. High-dimensional mixed frequency time-series data can also be easily manipulated with functions provided in the package.

Maintained by Jonas Striaukas. Last updated 2 years ago.

forecasting-modelsmachine-learningnowcasting-modelssparse-group-lassotime-seriesfortran

37 stars 4.39 score 5 scripts

vwmaus

twdtw:Time-Weighted Dynamic Time Warping

Implements Time-Weighted Dynamic Time Warping (TWDTW), a measure for quantifying time series similarity. The TWDTW algorithm, described in Maus et al. (2016) <doi:10.1109/JSTARS.2016.2517118> and Maus et al. (2019) <doi:10.18637/jss.v088.i05>, is applicable to multi-dimensional time series of various resolutions. It is particularly suitable for comparing time series with seasonality for environmental and ecological data analysis, covering domains such as remote sensing imagery, climate data, hydrology, and animal movement. The 'twdtw' package offers a user-friendly 'R' interface, efficient 'Fortran' routines for TWDTW calculations, flexible time weighting definitions, as well as utilities for time series preprocessing and visualization.

Maintained by Victor Maus. Last updated 1 years ago.

fortrancpp

8 stars 4.38 score 2 scripts 2 dependents

cran

Rfit:Rank-Based Estimation for Linear Models

Rank-based (R) estimation and inference for linear models. Estimation is for general scores and a library of commonly used score functions is included.

Maintained by John Kloke. Last updated 10 months ago.

fortran

4.35 score 9 dependents

syksy

oscar:Optimal Subset Cardinality Regression (OSCAR) Models Using the L0-Pseudonorm

Optimal Subset Cardinality Regression (OSCAR) models offer regularized linear regression using the L0-pseudonorm, conventionally known as the number of non-zero coefficients. The package estimates an optimal subset of features using the L0-penalization via cross-validation, bootstrapping and visual diagnostics. Effective Fortran implementations are offered along the package for finding optima for the DC-decomposition, which is used for transforming the discrete L0-regularized optimization problem into a continuous non-convex optimization task. These optimization modules include DBDC ('Double Bundle method for nonsmooth DC optimization' as described in Joki et al. (2018) <doi:10.1137/16M1115733>) and LMBM ('Limited Memory Bundle Method for large-scale nonsmooth optimization' as in Haarala et al. (2004) <doi:10.1080/10556780410001689225>). The OSCAR models are comprehensively exemplified in Halkola et al. (2023) <doi:10.1371/journal.pcbi.1010333>). Multiple regression model families are supported: Cox, logistic, and Gaussian.

Maintained by Teemu Daniel Laajala. Last updated 1 years ago.

fortranpenalized-regressionregression

2 stars 4.34 score 11 scripts

wmay

oc:Optimal Classification Roll Call Analysis Software

Estimates optimal classification (Poole 2000) <doi:10.1093/oxfordjournals.pan.a029814> scores from roll call votes supplied though a 'rollcall' object from package 'pscl'.

Maintained by William May. Last updated 2 years ago.

fortranideal-pointspolitical-scienceopenblas

2 stars 4.30 score 50 scripts

bioc

CNAnorm:A normalization method for Copy Number Aberration in cancer samples

Performs ratio, GC content correction and normalization of data obtained using low coverage (one read every 100-10,000 bp) high troughput sequencing. It performs a "discrete" normalization looking for the ploidy of the genome. It will also provide tumour content if at least two ploidy states can be found.

Maintained by Stefano Berri. Last updated 5 months ago.

copynumbervariationsequencingcoveragenormalizationwholegenomednaseqgenomicvariationfortran

4.30 score 6 scripts

snoweye

pbdSLAP:Programming with Big Data -- Scalable Linear Algebra Packages

Utilizing scalable linear algebra packages mainly including 'BLACS', 'PBLAS', and 'ScaLAPACK' in double precision via 'pbdMPI' based on 'ScaLAPACK' version 2.0.2.

Maintained by Wei-Chen Chen. Last updated 5 months ago.

fortranopenmpi

4.30 score 4 scripts

bluegreen-labs

igrf:International Geomagnetic Reference Field

The 13th generation International Geomagnetic Reference Field (IGRF). A standard spherical harmonic representation of the Earth's main field.

Maintained by Koen Hufkens. Last updated 1 years ago.

geomagnetic-fieldmovement-ecologyfortran

4 stars 4.30 score 3 scripts

egarpor

DirStats:Nonparametric Methods for Directional Data

Nonparametric kernel density estimation, bandwidth selection, and other utilities for analyzing directional data. Implements the estimator in Bai, Rao and Zhao (1987) <doi:10.1016/0047-259X(88)90113-3>, the cross-validation bandwidth selectors in Hall, Watson and Cabrera (1987) <doi:10.1093/biomet/74.4.751> and the plug-in bandwidth selectors in García-Portugués (2013) <doi:10.1214/13-ejs821>.

Maintained by Eduardo García-Portugués. Last updated 2 years ago.

directional-statisticsnonparametric-statisticsstatisticsfortran

12 stars 4.26 score 7 scripts 1 dependents

nano-optics

mie:Mie scattering

Numerical implementation of Mie scattering theory for light scattering by spherical particles.

Maintained by Baptiste Auguie. Last updated 2 years ago.

fortran

8 stars 4.26 score 15 scripts

hanase

mlogitBMA:Bayesian Model Averaging for Multinomial Logit Models

Provides a modified function bic.glm of the BMA package that can be applied to multinomial logit (MNL) data. The data is converted to binary logit using the Begg & Gray approximation. The package also contains functions for maximum likelihood estimation of MNL.

Maintained by Hana Sevcikova. Last updated 5 months ago.

fortran

4.26 score 18 scripts

cran

mix:Estimation/Multiple Imputation for Mixed Categorical and Continuous Data

Estimation/multiple imputation programs for mixed categorical and continuous data.

Maintained by Brian Ripley. Last updated 4 months ago.

fortran

2 stars 4.21 score 5 dependents

vmoprojs

GeoModels:Procedures for Gaussian and Non Gaussian Geostatistical (Large) Data Analysis

Functions for Gaussian and Non Gaussian (bivariate) spatial and spatio-temporal data analysis are provided for a) (fast) simulation of random fields, b) inference for random fields using standard likelihood and a likelihood approximation method called weighted composite likelihood based on pairs and b) prediction using (local) best linear unbiased prediction. Weighted composite likelihood can be very efficient for estimating massive datasets. Both regression and spatial (temporal) dependence analysis can be jointly performed. Flexible covariance models for spatial and spatial-temporal data on Euclidean domains and spheres are provided. There are also many useful functions for plotting and performing diagnostic analysis. Different non Gaussian random fields can be considered in the analysis. Among them, random fields with marginal distributions such as Skew-Gaussian, Student-t, Tukey-h, Sin-Arcsin, Two-piece, Weibull, Gamma, Log-Gaussian, Binomial, Negative Binomial and Poisson. See the URL for the papers associated with this package, as for instance, Bevilacqua and Gaetan (2015) <doi:10.1007/s11222-014-9460-6>, Bevilacqua et al. (2016) <doi:10.1007/s13253-016-0256-3>, Vallejos et al. (2020) <doi:10.1007/978-3-030-56681-4>, Bevilacqua et. al (2020) <doi:10.1002/env.2632>, Bevilacqua et. al (2021) <doi:10.1111/sjos.12447>, Bevilacqua et al. (2022) <doi:10.1016/j.jmva.2022.104949>, Morales-Navarrete et al. (2023) <doi:10.1080/01621459.2022.2140053>, and a large class of examples and tutorials.

Maintained by Moreno Bevilacqua. Last updated 2 months ago.

fortranopenblasglibc

3 stars 4.17 score 83 scripts

ucl

RefBasedMI:Reference-Based Imputation for Longitudinal Clinical Trials with Protocol Deviation

Imputation of missing numerical outcomes for a longitudinal trial with protocol deviations. The package uses distinct treatment arm-based assumptions for the unobserved data, following the general algorithm of Carpenter, Roger, and Kenward (2013) <doi:10.1080/10543406.2013.834911>, and the causal model of White, Royes and Best (2020) <doi:10.1080/10543406.2019.1684308>. Sensitivity analyses to departures from these assumptions can be done by the Delta method of Roger. The program uses the same algorithm as the 'mimix' 'Stata' package written by Suzie Cro, with additional coding for the causal model and delta method. The reference-based methods are jump to reference (J2R), copy increments in reference (CIR), copy reference (CR), and the causal model, all of which must specify the reference treatment arm. Other methods are missing at random (MAR) and the last mean carried forward (LMCF). Individual-specific imputation methods (and their reference groups) can be specified.

Maintained by Matteo Quartagno. Last updated 7 months ago.

fortran

3 stars 4.13 score 3 scripts

jarioksa

twinspan:Two-Way Indicator Species Analysis

Classification of biological communities based on splitting first axis of Correspondence Analysis for the current subset of the data, and finding species that best indicate the splits. The method is particularly popular in vegetation science.

Maintained by Jari Oksanen. Last updated 4 months ago.

fortran

7 stars 4.10 score 18 scripts

jlaake

marked:Mark-Recapture Analysis for Survival and Abundance Estimation

Functions for fitting various models to capture-recapture data including mixed-effects Cormack-Jolly-Seber(CJS) and multistate models and the multi-variate state model structure for survival estimation and POPAN structured Jolly-Seber models for abundance estimation. There are also Hidden Markov model (HMM) implementations of CJS and multistate models with and without state uncertainty and a simulation capability for HMM models.

Maintained by Jeff Laake. Last updated 1 years ago.

fortrancpp

1 stars 4.09 score 85 scripts 1 dependents

karlines

OceanView:Visualisation of Oceanographic Data and Model Output

Functions for transforming and viewing 2-D and 3-D (oceanographic) data and model output.

Maintained by Karline Soetaert. Last updated 1 years ago.

fortran

4.08 score 60 scripts

sandracastropearson

BivRec:Bivariate Alternating Recurrent Event Data Analysis

A collection of models for bivariate alternating recurrent event data analysis. Includes non-parametric and semi-parametric methods.

Maintained by Sandra Castro-Pearson. Last updated 4 years ago.

fortran

2 stars 4.07 score 39 scripts

cran

logspline:Routines for Logspline Density Estimation

Contains routines for logspline density estimation. The function oldlogspline() uses the same algorithm as the logspline package version 1.0.x; i.e. the Kooperberg and Stone (1992) algorithm (with an improved interface). The recommended routine logspline() uses an algorithm from Stone et al (1997) <DOI:10.1214/aos/1031594728>.

Maintained by Charles Kooperberg. Last updated 11 months ago.

fortranopenblas

4.03 score 13 dependents

hckiang

glinvci:Phylogenetic Comparative Methods with Uncertainty Estimates

A framework for analytically computing the asymptotic confidence intervals and maximum-likelihood estimates of a class of continuous-time Gaussian branching processes defined by Mitov V, Bartoszek K, Asimomitis G, Stadler T (2019) <doi:10.1016/j.tpb.2019.11.005>. The class of model includes the widely used Ornstein-Uhlenbeck and Brownian motion branching processes. The framework is designed to be flexible enough so that the users can easily specify their own sub-models, or re-parameterizations, and obtain the maximum-likelihood estimates and confidence intervals of their own custom models.

Maintained by Woodrow Kiang. Last updated 12 months ago.

fortranopenblasopenmp

4.00 score 5 scripts

ly129

ktweedie:'Tweedie' Compound Poisson Model in the Reproducing Kernel Hilbert Space

Kernel-based 'Tweedie' compound Poisson gamma model using high-dimensional predictors for the analyses of zero-inflated response variables. The package features built-in estimation, prediction and cross-validation tools and supports choice of different kernel functions. For more details, please see Yi Lian, Archer Yi Yang, Boxiang Wang, Peng Shi & Robert William Platt (2023) <doi:10.1080/00401706.2022.2156615>.

Maintained by Yi Lian. Last updated 1 years ago.

fortran

2 stars 4.00 score 5 scripts

vochr

rBDAT:Implementation of BDAT Tree Taper Fortran Functions

Implementing the BDAT tree taper Fortran routines, which were developed for the German National Forest Inventory (NFI), to calculate diameters, volume, assortments, double bark thickness and biomass for different tree species based on tree characteristics and sorting information. See Kublin (2003) <doi:10.1046/j.1439-0337.2003.00183.x> for details.

Maintained by Christian Vonderach. Last updated 6 months ago.

fortran

4.00 score 8 scripts

boennecd

mmcif:Mixed Multivariate Cumulative Incidence Functions

Fits the mixed cumulative incidence functions model suggested by <doi:10.1093/biostatistics/kxx072> which decomposes within cluster dependence of risk and timing. The estimation method supports computation in parallel using a shared memory C++ implementation. A sandwich estimator of the covariance matrix is available. Natural cubic splines are used to provide a flexible model for the cumulative incidence functions.

Maintained by Benjamin Christoffersen. Last updated 2 years ago.

competing-riskcomposite-likelihoodmixed-modelssandwich-estimatorsurvival-analysisfortranopenblascppopenmp

4.00 score 10 scripts

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