R-universe search: standards

easystats

effectsize:Indices of Effect Size

Provide utilities to work with indices of effect size for a wide variety of models and hypothesis tests (see list of supported models using the function 'insight::supported_models()'), allowing computation of and conversion between indices such as Cohen's d, r, odds, etc. References: Ben-Shachar et al. (2020) <doi:10.21105/joss.02815>.

Maintained by Mattan S. Ben-Shachar. Last updated 1 months ago.

anova cohens-d compute conversion correlation effect-size effectsize hacktoberfest hedges-g interpretation standardization standardized statistics

43.0 match 344 stars 16.38 score 1.8k scripts 29 dependents

elvanceyhan

pcds:Proximity Catch Digraphs and Their Applications

Contains the functions for construction and visualization of various families of the proximity catch digraphs (PCDs) (see (Ceyhan (2005) ISBN:978-3-639-19063-2), for computing the graph invariants for testing the patterns of segregation and association against complete spatial randomness (CSR) or uniformity in one, two and three dimensional cases. The package also has tools for generating points from these spatial patterns. The graph invariants used in testing spatial point data are the domination number (Ceyhan (2011) <doi:10.1080/03610921003597211>) and arc density (Ceyhan et al. (2006) <doi:10.1016/j.csda.2005.03.002>; Ceyhan et al. (2007) <doi:10.1002/cjs.5550350106>). The PCD families considered are Arc-Slice PCDs, Proportional-Edge PCDs, and Central Similarity PCDs.

Maintained by Elvan Ceyhan. Last updated 2 years ago.

105.1 match 5.80 score 21 scripts 2 dependents

cdeager

standardize:Tools for Standardizing Variables for Regression in R

Tools which allow regression variables to be placed on similar scales, offering computational benefits as well as easing interpretation of regression output.

Maintained by Christopher D. Eager. Last updated 4 years ago.

83.8 match 23 stars 6.50 score 92 scripts 1 dependents

dfsp-spirit

fsbrain:Managing and Visualizing Brain Surface Data

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

Maintained by Tim Schäfer. Last updated 4 months ago.

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

66.0 match 66 stars 6.47 score 15 scripts

easystats

parameters:Processing of Model Parameters

Utilities for processing the parameters of various statistical models. Beyond computing p values, CIs, and other indices for a wide variety of models (see list of supported models using the function 'insight::supported_models()'), this package implements features like bootstrapping or simulating of parameters and models, feature reduction (feature extraction and variable selection) as well as functions to describe data and variable characteristics (e.g. skewness, kurtosis, smoothness or distribution).

Maintained by Daniel Lüdecke. Last updated 2 days ago.

beta bootstrap ci confidence-intervals data-reduction easystats fa feature-extraction feature-reduction hacktoberfest parameters pca pvalues regression-models robust-statistics standardize standardized-estimates statistical-models

24.0 match 453 stars 15.65 score 1.8k scripts 56 dependents

yelleknek

MBESS:The MBESS R Package

Implements methods that are useful in designing research studies and analyzing data, with particular emphasis on methods that are developed for or used within the behavioral, educational, and social sciences (broadly defined). That being said, many of the methods implemented within MBESS are applicable to a wide variety of disciplines. MBESS has a suite of functions for a variety of related topics, such as effect sizes, confidence intervals for effect sizes (including standardized effect sizes and noncentral effect sizes), sample size planning (from the accuracy in parameter estimation [AIPE], power analytic, equivalence, and minimum-risk point estimation perspectives), mediation analysis, various properties of distributions, and a variety of utility functions. MBESS (pronounced 'em-bes') was originally an acronym for 'Methods for the Behavioral, Educational, and Social Sciences,' but MBESS became more general and now contains methods applicable and used in a wide variety of fields and is an orphan acronym, in the sense that what was an acronym is now literally its name. MBESS has greatly benefited from others, see <https://www3.nd.edu/~kkelley/site/MBESS.html> for a detailed list of those that have contributed and other details.

Maintained by Ken Kelley. Last updated 1 years ago.

41.7 match 2 stars 8.21 score 274 scripts 23 dependents

glenndavis52

colorSpec:Color Calculations with Emphasis on Spectral Data

Calculate with spectral properties of light sources, materials, cameras, eyes, and scanners. Build complex systems from simpler parts using a spectral product algebra. For light sources, compute CCT, CRI, SSI, and IES TM-30 reports. For object colors, compute optimal colors and Logvinenko coordinates. Work with the standard CIE illuminants and color matching functions, and read spectra from text files, including CGATS files. Estimate a spectrum from its response. A user guide and 9 vignettes are included.

Maintained by Glenn Davis. Last updated 1 months ago.

48.8 match 2 stars 6.34 score 73 scripts 5 dependents

sfcheung

stdmod:Standardized Moderation Effect and Its Confidence Interval

Functions for computing a standardized moderation effect in moderated regression and forming its confidence interval by nonparametric bootstrapping as proposed in Cheung, Cheung, Lau, Hui, and Vong (2022) <doi:10.1037/hea0001188>. Also includes simple-to-use functions for computing conditional effects (unstandardized or standardized) and plotting moderation effects.

Maintained by Shu Fai Cheung. Last updated 6 months ago.

bootstrapping confidence-interval effect-sizes moderation regression standardization standardized-moderation

50.4 match 1 stars 5.62 score 46 scripts

ropensci

gigs:Assess Fetal, Newborn, and Child Growth with International Standards

Convert between anthropometric measures and z-scores/centiles in multiple growth standards, and classify fetal, newborn, and child growth accordingly. With a simple interface to growth standards from the World Health Organisation and International Fetal and Newborn Growth Consortium for the 21st Century, gigs makes growth assessment easy and reproducible for clinicians, researchers and policy-makers.

Maintained by Simon R Parker. Last updated 25 days ago.

anthropometry growth-standards intergrowth who

62.9 match 4 stars 4.38 score 8 scripts

lrberge

fixest:Fast Fixed-Effects Estimations

Fast and user-friendly estimation of econometric models with multiple fixed-effects. Includes ordinary least squares (OLS), generalized linear models (GLM) and the negative binomial. The core of the package is based on optimized parallel C++ code, scaling especially well for large data sets. The method to obtain the fixed-effects coefficients is based on Berge (2018) <https://github.com/lrberge/fixest/blob/master/_DOCS/FENmlm_paper.pdf>. Further provides tools to export and view the results of several estimations with intuitive design to cluster the standard-errors.

Maintained by Laurent Berge. Last updated 7 months ago.

cpp openmp

17.4 match 387 stars 14.69 score 3.8k scripts 25 dependents

ropengov

rqog:Download data from the Quality of Government Institute data

R client for the Quality of Government (QOG) open data. Client can be used to fetch data files <https://qog.pol.gu.se/data> and converted into data.frame objects in R.

Maintained by Markus Kainu. Last updated 2 years ago.

ropengov data-package

53.3 match 15 stars 4.22 score 22 scripts

alanarnholt

BSDA:Basic Statistics and Data Analysis

Data sets for book "Basic Statistics and Data Analysis" by Larry J. Kitchens.

Maintained by Alan T. Arnholt. Last updated 2 years ago.

23.5 match 7 stars 9.11 score 1.3k scripts 6 dependents

hadley

lazyeval:Lazy (Non-Standard) Evaluation

An alternative approach to non-standard evaluation using formulas. Provides a full implementation of LISP style 'quasiquotation', making it easier to generate code with other code.

Maintained by Hadley Wickham. Last updated 3 years ago.

12.5 match 131 stars 15.74 score 520 scripts 1.8k 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 3 days ago.

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

14.3 match 14 stars 13.47 score 236 scripts 42 dependents

sizespectrum

mizer:Dynamic Multi-Species Size Spectrum Modelling

A set of classes and methods to set up and run multi-species, trait based and community size spectrum ecological models, focused on the marine environment.

Maintained by Gustav Delius. Last updated 2 months ago.

ecosystem-model fish-population-dynamics fisheries fisheries-management marine-ecosystem population-dynamics simulation size-structure species-interactions transport-equation cpp

20.0 match 38 stars 9.43 score 207 scripts

dewittpe

pedbp:Pediatric Blood Pressure

Data and utilities for estimating pediatric blood pressure percentiles by sex, age, and optionally height (stature) as described in Martin et.al. (2022) <doi:10.1001/jamanetworkopen.2022.36918>. Blood pressure percentiles for children under one year of age come from Gemelli et.al. (1990) <doi:10.1007/BF02171556>. Estimates of blood pressure percentiles for children at least one year of age are informed by data from the National Heart, Lung, and Blood Institute (NHLBI) and the Centers for Disease Control and Prevention (CDC) <doi:10.1542/peds.2009-2107C> or from Lo et.al. (2013) <doi:10.1542/peds.2012-1292>. The flowchart for selecting the informing data source comes from Martin et.al. (2022) <doi:10.1542/hpeds.2021-005998>.

Maintained by Peter DeWitt. Last updated 2 months ago.

blood-pressure growth-standards pediatric cpp

28.7 match 6 stars 6.43 score 45 scripts

jacob-long

jtools:Analysis and Presentation of Social Scientific Data

This is a collection of tools for more efficiently understanding and sharing the results of (primarily) regression analyses. There are also a number of miscellaneous functions for statistical and programming purposes. Support for models produced by the survey and lme4 packages are points of emphasis.

Maintained by Jacob A. Long. Last updated 6 months ago.

social-sciences

12.7 match 167 stars 14.48 score 4.0k scripts 14 dependents

braverock

PerformanceAnalytics:Econometric Tools for Performance and Risk Analysis

Collection of econometric functions for performance and risk analysis. In addition to standard risk and performance metrics, this package aims to aid practitioners and researchers in utilizing the latest research in analysis of non-normal return streams. In general, it is most tested on return (rather than price) data on a regular scale, but most functions will work with irregular return data as well, and increasing numbers of functions will work with P&L or price data where possible.

Maintained by Brian G. Peterson. Last updated 3 months ago.

11.3 match 222 stars 15.93 score 4.8k scripts 20 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 19 days ago.

fortran

15.1 match 39 stars 11.71 score 546 scripts 26 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 30 days ago.

brain mri mrs mrshub spectroscopy fortran

19.1 match 25 stars 8.52 score 81 scripts

kosukeimai

MatchIt:Nonparametric Preprocessing for Parametric Causal Inference

Selects matched samples of the original treated and control groups with similar covariate distributions -- can be used to match exactly on covariates, to match on propensity scores, or perform a variety of other matching procedures. The package also implements a series of recommendations offered in Ho, Imai, King, and Stuart (2007) <DOI:10.1093/pan/mpl013>. (The 'gurobi' package, which is not on CRAN, is optional and comes with an installation of the Gurobi Optimizer, available at <https://www.gurobi.com>.)

Maintained by Noah Greifer. Last updated 2 days ago.

cpp openmp

10.8 match 220 stars 15.03 score 2.4k scripts 21 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 7 hours ago.

fortran cpp

9.6 match 87 stars 16.70 score 7.7k scripts 99 dependents

rpolars

polars:Lightning-Fast 'DataFrame' Library

Lightning-fast 'DataFrame' library written in 'Rust'. Convert R data to 'Polars' data and vice versa. Perform fast, lazy, larger-than-memory and optimized data queries. 'Polars' is interoperable with the package 'arrow', as both are based on the 'Apache Arrow' Columnar Format.

Maintained by Soren Welling. Last updated 3 days ago.

arrow polars rust

13.3 match 499 stars 12.01 score 1.0k scripts 2 dependents

dgbonett

vcmeta:Varying Coefficient Meta-Analysis

Implements functions for varying coefficient meta-analysis methods. These methods do not assume effect size homogeneity. Subgroup effect size comparisons, general linear effect size contrasts, and linear models of effect sizes based on varying coefficient methods can be used to describe effect size heterogeneity. Varying coefficient meta-analysis methods do not require the unrealistic assumptions of the traditional fixed-effect and random-effects meta-analysis methods. For details see: Statistical Methods for Psychologists, Volume 5, <https://dgbonett.sites.ucsc.edu/>.

Maintained by Douglas G. Bonett. Last updated 8 months ago.

51.8 match 1 stars 3.00 score 8 scripts

sachsmc

stdReg2:Regression Standardization for Causal Inference

Contains more modern tools for causal inference using regression standardization. Four general classes of models are implemented; generalized linear models, conditional generalized estimating equation models, Cox proportional hazards models, and shared frailty gamma-Weibull models. Methodological details are described in Sjölander, A. (2016) <doi:10.1007/s10654-016-0157-3>. Also includes functionality for doubly robust estimation for generalized linear models in some special cases, and the ability to implement custom models.

Maintained by Michael C Sachs. Last updated 16 days ago.

30.5 match 2 stars 5.08 score 9 scripts

acdelre

MAd:Meta-Analysis with Mean Differences

A collection of functions for conducting a meta-analysis with mean differences data. It uses recommended procedures as described in The Handbook of Research Synthesis and Meta-Analysis (Cooper, Hedges, & Valentine, 2009).

Maintained by AC Del Re. Last updated 3 years ago.

34.3 match 4.29 score 82 scripts 2 dependents

pln-team

PLNmodels:Poisson Lognormal Models

The Poisson-lognormal model and variants (Chiquet, Mariadassou and Robin, 2021 <doi:10.3389/fevo.2021.588292>) can be used for a variety of multivariate problems when count data are at play, including principal component analysis for count data, discriminant analysis, model-based clustering and network inference. Implements variational algorithms to fit such models accompanied with a set of functions for visualization and diagnostic.

Maintained by Julien Chiquet. Last updated 4 days ago.

count-data multivariate-analysis network-inference pca poisson-lognormal-model openblas cpp

15.0 match 56 stars 9.50 score 226 scripts

dgbonett

statpsych:Statistical Methods for Psychologists

Implements confidence interval and sample size methods that are especially useful in psychological research. The methods can be applied in 1-group, 2-group, paired-samples, and multiple-group designs and to a variety of parameters including means, medians, proportions, slopes, standardized mean differences, standardized linear contrasts of means, plus several measures of correlation and association. Confidence interval and sample size functions are given for single parameters as well as differences, ratios, and linear contrasts of parameters. The sample size functions can be used to approximate the sample size needed to estimate a parameter or function of parameters with desired confidence interval precision or to perform a variety of hypothesis tests (directional two-sided, equivalence, superiority, noninferiority) with desired power. For details see: Statistical Methods for Psychologists, Volumes 1 – 4, <https://dgbonett.sites.ucsc.edu/>.

Maintained by Douglas G. Bonett. Last updated 3 months ago.

29.5 match 6 stars 4.83 score 15 scripts 1 dependents

jeksterslab

betaSandwich:Robust Confidence Intervals for Standardized Regression Coefficients

Generates robust confidence intervals for standardized regression coefficients using heteroskedasticity-consistent standard errors for models fitted by lm() as described in Dudgeon (2017) <doi:10.1007/s11336-017-9563-z>. The package can also be used to generate confidence intervals for R-squared, adjusted R-squared, and differences of standardized regression coefficients. A description of the package and code examples are presented in Pesigan, Sun, and Cheung (2023) <doi:10.1080/00273171.2023.2201277>.

Maintained by Ivan Jacob Agaloos Pesigan. Last updated 2 months ago.

confidence-intervals heteroskedasticity-consistent-standard-errors standardized-regression-coefficients

34.2 match 4.16 score 16 scripts

alexkowa

EnvStats:Package for Environmental Statistics, Including US EPA Guidance

Graphical and statistical analyses of environmental data, with focus on analyzing chemical concentrations and physical parameters, usually in the context of mandated environmental monitoring. Major environmental statistical methods found in the literature and regulatory guidance documents, with extensive help that explains what these methods do, how to use them, and where to find them in the literature. Numerous built-in data sets from regulatory guidance documents and environmental statistics literature. Includes scripts reproducing analyses presented in the book "EnvStats: An R Package for Environmental Statistics" (Millard, 2013, Springer, ISBN 978-1-4614-8455-4, <doi:10.1007/978-1-4614-8456-1>).

Maintained by Alexander Kowarik. Last updated 17 days ago.

10.9 match 26 stars 12.80 score 2.4k scripts 46 dependents

corentinjgosling

metaConvert:An Automatic Suite for Estimation of Various Effect Size Measures

Automatically estimate 11 effect size measures from a well-formatted dataset. Various other functions can help, for example, removing dependency between several effect sizes, or identifying differences between two datasets. This package is mainly designed to assist in conducting a systematic review with a meta-analysis but can be useful to any researcher interested in estimating an effect size.

Maintained by Corentin J. Gosling. Last updated 4 months ago.

43.9 match 3.18 score 3 scripts

bradyajohnston

standard:Simplified Fitting and Use of Standard Curves

{standard} provices a more simplified interface to the linear models system in R for the fitting of standard curves and their usage in biochemistry and molecular biology.

Maintained by Brady Johnston. Last updated 1 years ago.

69.7 match 1.98 score 19 scripts

tbates

umx:Structural Equation Modeling and Twin Modeling in R

Quickly create, run, and report structural equation models, and twin models. See '?umx' for help, and umx_open_CRAN_page("umx") for NEWS. Timothy C. Bates, Michael C. Neale, Hermine H. Maes, (2019). umx: A library for Structural Equation and Twin Modelling in R. Twin Research and Human Genetics, 22, 27-41. <doi:10.1017/thg.2019.2>.

Maintained by Timothy C. Bates. Last updated 2 days ago.

behavior-genetics genetics openmx psychology sem statistics structural-equation-modeling tutorials twin-models umx

14.6 match 44 stars 9.45 score 472 scripts

stan-dev

posterior:Tools for Working with Posterior Distributions

Provides useful tools for both users and developers of packages for fitting Bayesian models or working with output from Bayesian models. The primary goals of the package are to: (a) Efficiently convert between many different useful formats of draws (samples) from posterior or prior distributions. (b) Provide consistent methods for operations commonly performed on draws, for example, subsetting, binding, or mutating draws. (c) Provide various summaries of draws in convenient formats. (d) Provide lightweight implementations of state of the art posterior inference diagnostics. References: Vehtari et al. (2021) <doi:10.1214/20-BA1221>.

Maintained by Paul-Christian Bürkner. Last updated 10 days ago.

bayes bayesian mcmc

8.4 match 168 stars 16.13 score 3.3k scripts 342 dependents

tomasfryda

h2o:R Interface for the 'H2O' Scalable Machine Learning Platform

R interface for 'H2O', the scalable open source machine learning platform that offers parallelized implementations of many supervised and unsupervised machine learning algorithms such as Generalized Linear Models (GLM), Gradient Boosting Machines (including XGBoost), Random Forests, Deep Neural Networks (Deep Learning), Stacked Ensembles, Naive Bayes, Generalized Additive Models (GAM), ANOVA GLM, Cox Proportional Hazards, K-Means, PCA, ModelSelection, Word2Vec, as well as a fully automatic machine learning algorithm (H2O AutoML).

Maintained by Tomas Fryda. Last updated 1 years ago.

16.5 match 3 stars 8.20 score 7.8k scripts 11 dependents

robertemprechtinger

metaHelper:Transforms Statistical Measures Commonly Used for Meta-Analysis

Helps calculate statistical values commonly used in meta-analysis. It provides several methods to compute different forms of standardized mean differences, as well as other values such as standard errors and standard deviations. The methods used in this package are described in the following references: Altman D G, Bland J M. (2011) <doi:10.1136/bmj.d2090> Borenstein, M., Hedges, L.V., Higgins, J.P.T. and Rothstein, H.R. (2009) <doi:10.1002/9780470743386.ch4> Chinn S. (2000) <doi:10.1002/1097-0258(20001130)19:22%3C3127::aid-sim784%3E3.0.co;2-m> Cochrane Handbook (2011) <https://handbook-5-1.cochrane.org/front_page.htm> Cooper, H., Hedges, L. V., & Valentine, J. C. (2009) <https://psycnet.apa.org/record/2009-05060-000> Cohen, J. (1977) <https://psycnet.apa.org/record/1987-98267-000> Ellis, P.D. (2009) <https://www.psychometrica.de/effect_size.html> Goulet-Pelletier, J.-C., & Cousineau, D. (2018) <doi:10.20982/tqmp.14.4.p242> Hedges, L. V. (1981) <doi:10.2307/1164588> Hedges L. V., Olkin I. (1985) <doi:10.1016/C2009-0-03396-0> Murad M H, Wang Z, Zhu Y, Saadi S, Chu H, Lin L et al. (2023) <doi:10.1136/bmj-2022-073141> Mayer M (2023) <https://search.r-project.org/CRAN/refmans/confintr/html/ci_proportion.html> Stackoverflow (2014) <https://stats.stackexchange.com/questions/82720/confidence-interval-around-binomial-estimate-of-0-or-1> Stackoverflow (2018) <https://stats.stackexchange.com/q/338043>.

Maintained by Robert Emprechtinger. Last updated 8 months ago.

34.6 match 4 stars 3.90 score

radiant-rstats

radiant.data:Data Menu for Radiant: Business Analytics using R and Shiny

The Radiant Data menu includes interfaces for loading, saving, viewing, visualizing, summarizing, transforming, and combining data. It also contains functionality to generate reproducible reports of the analyses conducted in the application.

Maintained by Vincent Nijs. Last updated 5 months ago.

16.3 match 54 stars 8.30 score 146 scripts 6 dependents

mrcieu

TwoSampleMR:Two Sample MR Functions and Interface to MRC Integrative Epidemiology Unit OpenGWAS Database

A package for performing Mendelian randomization using GWAS summary data. It uses the IEU OpenGWAS database <https://gwas.mrcieu.ac.uk/> to automatically obtain data, and a wide range of methods to run the analysis.

Maintained by Gibran Hemani. Last updated 10 days ago.

11.8 match 467 stars 11.23 score 1.7k scripts 1 dependents

florianhartig

BayesianTools:General-Purpose MCMC and SMC Samplers and Tools for Bayesian Statistics

General-purpose MCMC and SMC samplers, as well as plots and diagnostic functions for Bayesian statistics, with a particular focus on calibrating complex system models. Implemented samplers include various Metropolis MCMC variants (including adaptive and/or delayed rejection MH), the T-walk, two differential evolution MCMCs, two DREAM MCMCs, and a sequential Monte Carlo (SMC) particle filter.

Maintained by Florian Hartig. Last updated 1 years ago.

bayes ecological-models mcmc optimization smc systems-biology cpp

12.9 match 122 stars 10.17 score 580 scripts 5 dependents

jeksterslab

betaDelta:Confidence Intervals for Standardized Regression Coefficients

Generates confidence intervals for standardized regression coefficients using delta method standard errors for models fitted by lm() as described in Yuan and Chan (2011) <doi:10.1007/s11336-011-9224-6> and Jones and Waller (2015) <doi:10.1007/s11336-013-9380-y>. The package can also be used to generate confidence intervals for differences of standardized regression coefficients and as a general approach to performing the delta method. A description of the package and code examples are presented in Pesigan, Sun, and Cheung (2023) <doi:10.1080/00273171.2023.2201277>.

Maintained by Ivan Jacob Agaloos Pesigan. Last updated 2 months ago.

confidence-intervals delta-method-standard-errors standardized-regression-coefficients

31.1 match 4.20 score 20 scripts

philchalmers

SimDesign:Structure for Organizing Monte Carlo Simulation Designs

Provides tools to safely and efficiently organize and execute Monte Carlo simulation experiments in R. The package controls the structure and back-end of Monte Carlo simulation experiments by utilizing a generate-analyse-summarise workflow. The workflow safeguards against common simulation coding issues, such as automatically re-simulating non-convergent results, prevents inadvertently overwriting simulation files, catches error and warning messages during execution, implicitly supports parallel processing with high-quality random number generation, and provides tools for managing high-performance computing (HPC) array jobs submitted to schedulers such as SLURM. For a pedagogical introduction to the package see Sigal and Chalmers (2016) <doi:10.1080/10691898.2016.1246953>. For a more in-depth overview of the package and its design philosophy see Chalmers and Adkins (2020) <doi:10.20982/tqmp.16.4.p248>.

Maintained by Phil Chalmers. Last updated 19 hours ago.

monte-carlo-simulation simulation simulation-framework

9.5 match 62 stars 13.36 score 253 scripts 46 dependents

swissstatsr

dcatapchr:Create DCAT-AP CH Metadata Files

Create DCAT-AP CH metadata files, typically in rdf format.

Maintained by Sandro Burri. Last updated 3 months ago.

43.9 match 2.81 score 3 scripts

afialkowski

SimMultiCorrData:Simulation of Correlated Data with Multiple Variable Types

Generate continuous (normal or non-normal), binary, ordinal, and count (Poisson or Negative Binomial) variables with a specified correlation matrix. It can also produce a single continuous variable. This package can be used to simulate data sets that mimic real-world situations (i.e. clinical or genetic data sets, plasmodes). All variables are generated from standard normal variables with an imposed intermediate correlation matrix. Continuous variables are simulated by specifying mean, variance, skewness, standardized kurtosis, and fifth and sixth standardized cumulants using either Fleishman's third-order (<DOI:10.1007/BF02293811>) or Headrick's fifth-order (<DOI:10.1016/S0167-9473(02)00072-5>) polynomial transformation. Binary and ordinal variables are simulated using a modification of the ordsample() function from 'GenOrd'. Count variables are simulated using the inverse cdf method. There are two simulation pathways which differ primarily according to the calculation of the intermediate correlation matrix. In Correlation Method 1, the intercorrelations involving count variables are determined using a simulation based, logarithmic correlation correction (adapting Yahav and Shmueli's 2012 method, <DOI:10.1002/asmb.901>). In Correlation Method 2, the count variables are treated as ordinal (adapting Barbiero and Ferrari's 2015 modification of GenOrd, <DOI:10.1002/asmb.2072>). There is an optional error loop that corrects the final correlation matrix to be within a user-specified precision value of the target matrix. The package also includes functions to calculate standardized cumulants for theoretical distributions or from real data sets, check if a target correlation matrix is within the possible correlation bounds (given the distributions of the simulated variables), summarize results (numerically or graphically), to verify valid power method pdfs, and to calculate lower standardized kurtosis bounds.

Maintained by Allison Cynthia Fialkowski. Last updated 7 years ago.

16.3 match 12 stars 7.58 score 44 scripts 6 dependents

anthonychristidis

RPESE:Estimates of Standard Errors for Risk and Performance Measures

Estimates of standard errors of popular risk and performance measures for asset or portfolio returns using methods as described in Chen and Martin (2021) <doi:10.21314/JOR.2020.446>.

Maintained by Anthony Christidis. Last updated 7 months ago.

32.1 match 3.83 score 9 scripts

epiverse-trace

cleanepi:Clean and Standardize Epidemiological Data

Cleaning and standardizing tabular data package, tailored specifically for curating epidemiological data. It streamlines various data cleaning tasks that are typically expected when working with datasets in epidemiology. It returns the processed data in the same format, and generates a comprehensive report detailing the outcomes of each cleaning task.

Maintained by Karim Mané. Last updated 2 days ago.

data-cleaning epidemiology epiverse

15.9 match 9 stars 7.44 score 19 scripts

zhenkewu

baker:"Nested Partially Latent Class Models"

Provides functions to specify, fit and visualize nested partially-latent class models ( Wu, Deloria-Knoll, Hammitt, and Zeger (2016) <doi:10.1111/rssc.12101>; Wu, Deloria-Knoll, and Zeger (2017) <doi:10.1093/biostatistics/kxw037>; Wu and Chen (2021) <doi:10.1002/sim.8804>) for inference of population disease etiology and individual diagnosis. In the motivating Pneumonia Etiology Research for Child Health (PERCH) study, because both quantities of interest sum to one hundred percent, the PERCH scientists frequently refer to them as population etiology pie and individual etiology pie, hence the name of the package.

Maintained by Zhenke Wu. Last updated 11 months ago.

bayesian case-control latent-class-analysis jags cpp

19.3 match 8 stars 6.00 score 21 scripts

robinhankin

magic:Create and Investigate Magic Squares

A collection of functions for the manipulation and analysis of arbitrarily dimensioned arrays. The original motivation for the package was the development of efficient, vectorized algorithms for the creation and investigation of magic squares and high-dimensional magic hypercubes.

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

10.1 match 3 stars 11.12 score 436 scripts 230 dependents

sfcheung

manymome:Mediation, Moderation and Moderated-Mediation After Model Fitting

Computes indirect effects, conditional effects, and conditional indirect effects in a structural equation model or path model after model fitting, with no need to define any user parameters or label any paths in the model syntax, using the approach presented in Cheung and Cheung (2024) <doi:10.3758/s13428-023-02224-z>. Can also form bootstrap confidence intervals by doing bootstrapping only once and reusing the bootstrap estimates in all subsequent computations. Supports bootstrap confidence intervals for standardized (partially or completely) indirect effects, conditional effects, and conditional indirect effects as described in Cheung (2009) <doi:10.3758/BRM.41.2.425> and Cheung, Cheung, Lau, Hui, and Vong (2022) <doi:10.1037/hea0001188>. Model fitting can be done by structural equation modeling using lavaan() or regression using lm().

Maintained by Shu Fai Cheung. Last updated 23 days ago.

bootstrapping confidence-interval lavaan manymome mediation moderated-mediation moderation regression sem standardized-effect-size structural-equation-modeling

13.7 match 1 stars 8.06 score 172 scripts 4 dependents

cmsaf

cmsafops:Tools for CM SAF NetCDF Data

The Satellite Application Facility on Climate Monitoring (CM SAF) is a ground segment of the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) and one of EUMETSATs Satellite Application Facilities. The CM SAF contributes to the sustainable monitoring of the climate system by providing essential climate variables related to the energy and water cycle of the atmosphere (<https://www.cmsaf.eu>). It is a joint cooperation of eight National Meteorological and Hydrological Services. The 'cmsafops' R-package provides a collection of R-operators for the analysis and manipulation of CM SAF NetCDF formatted data. Other CF conform NetCDF data with time, longitude and latitude dimension should be applicable, but there is no guarantee for an error-free application. CM SAF climate data records are provided for free via (<https://wui.cmsaf.eu/safira>). Detailed information and test data are provided on the CM SAF webpage (<http://www.cmsaf.eu/R_toolbox>).

Maintained by Steffen Kothe. Last updated 6 months ago.

21.8 match 2 stars 5.03 score 4 scripts 2 dependents

eblondel

ows4R:Interface to OGC Web-Services (OWS)

Provides an Interface to Web-Services defined as standards by the Open Geospatial Consortium (OGC), including Web Feature Service (WFS) for vector data, Web Coverage Service (WCS), Catalogue Service (CSW) for ISO/OGC metadata, Web Processing Service (WPS) for data processes, and associated standards such as the common web-service specification (OWS) and OGC Filter Encoding. Partial support is provided for the Web Map Service (WMS). The purpose is to add support for additional OGC service standards such as Web Coverage Processing Service (WCPS), the Sensor Observation Service (SOS), or even new standard services emerging such OGC API or SensorThings.

Maintained by Emmanuel Blondel. Last updated 1 months ago.

catalogue-service csw dataaccess fes geospatial iso ogc ows sdi spatial spatial-data standard webfeatureservice wfs

12.0 match 38 stars 9.03 score 99 scripts 5 dependents

dvats

mcmcse:Monte Carlo Standard Errors for MCMC

Provides tools for computing Monte Carlo standard errors (MCSE) in Markov chain Monte Carlo (MCMC) settings. MCSE computation for expectation and quantile estimators is supported as well as multivariate estimations. The package also provides functions for computing effective sample size and for plotting Monte Carlo estimates versus sample size.

Maintained by Dootika Vats. Last updated 1 months ago.

effective-sample-size mcmc output-a openblas cpp

12.2 match 12 stars 8.77 score 314 scripts 17 dependents

bsvars

bsvars:Bayesian Estimation of Structural Vector Autoregressive Models

Provides fast and efficient procedures for Bayesian analysis of Structural Vector Autoregressions. This package estimates a wide range of models, including homo-, heteroskedastic, and non-normal specifications. Structural models can be identified by adjustable exclusion restrictions, time-varying volatility, or non-normality. They all include a flexible three-level equation-specific local-global hierarchical prior distribution for the estimated level of shrinkage for autoregressive and structural parameters. Additionally, the package facilitates predictive and structural analyses such as impulse responses, forecast error variance and historical decompositions, forecasting, verification of heteroskedasticity, non-normality, and hypotheses on autoregressive parameters, as well as analyses of structural shocks, volatilities, and fitted values. Beautiful plots, informative summary functions, and extensive documentation including the vignette by Woźniak (2024) <doi:10.48550/arXiv.2410.15090> complement all this. The implemented techniques align closely with those presented in Lütkepohl, Shang, Uzeda, & Woźniak (2024) <doi:10.48550/arXiv.2404.11057>, Lütkepohl & Woźniak (2020) <doi:10.1016/j.jedc.2020.103862>, and Song & Woźniak (2021) <doi:10.1093/acrefore/9780190625979.013.174>. The 'bsvars' package is aligned regarding objects, workflows, and code structure with the R package 'bsvarSIGNs' by Wang & Woźniak (2024) <doi:10.32614/CRAN.package.bsvarSIGNs>, and they constitute an integrated toolset.

Maintained by Tomasz Woźniak. Last updated 1 months ago.

bayesian-inference econometrics vector-autoregression openblas cpp openmp

13.6 match 46 stars 7.67 score 32 scripts 1 dependents

sfcheung

betaselectr:Betas-Select in Structural Equation Models and Linear Models

It computes betas-select, coefficients after standardization in structural equation models and regression models, standardizing only selected variables. Supports models with moderation, with product terms formed after standardization. It also offers confidence intervals that account for standardization, including bootstrap confidence intervals as proposed by Cheung et al. (2022) <doi:10.1037/hea0001188>.

Maintained by Shu Fai Cheung. Last updated 4 months ago.

bootstrapping confidence-intervals generalized-linear-models lavaan logistic-regression regression sem standardization structural-equation-modeling

21.0 match 1 stars 4.95 score 8 scripts

darwin-eu

CodelistGenerator:Identify Relevant Clinical Codes and Evaluate Their Use

Generate a candidate code list for the Observational Medical Outcomes Partnership (OMOP) common data model based on string matching. For a given search strategy, a candidate code list will be returned.

Maintained by Edward Burn. Last updated 25 days ago.

10.5 match 13 stars 9.87 score 165 scripts 4 dependents

cvxgrp

CVXR:Disciplined Convex Optimization

An object-oriented modeling language for disciplined convex programming (DCP) as described in Fu, Narasimhan, and Boyd (2020, <doi:10.18637/jss.v094.i14>). It allows the user to formulate convex optimization problems in a natural way following mathematical convention and DCP rules. The system analyzes the problem, verifies its convexity, converts it into a canonical form, and hands it off to an appropriate solver to obtain the solution. Interfaces to solvers on CRAN and elsewhere are provided, both commercial and open source.

Maintained by Anqi Fu. Last updated 4 months ago.

cpp

8.0 match 207 stars 12.89 score 768 scripts 51 dependents

suyusung

arm:Data Analysis Using Regression and Multilevel/Hierarchical Models

Functions to accompany A. Gelman and J. Hill, Data Analysis Using Regression and Multilevel/Hierarchical Models, Cambridge University Press, 2007.

Maintained by Yu-Sung Su. Last updated 5 months ago.

8.2 match 25 stars 12.38 score 3.3k scripts 89 dependents

bioc

metaMS:MS-based metabolomics annotation pipeline

MS-based metabolomics data processing and compound annotation pipeline.

Maintained by Yann Guitton. Last updated 5 months ago.

immunooncology massspectrometry metabolomics

13.6 match 15 stars 7.50 score 15 scripts

bioc

KBoost:Inference of gene regulatory networks from gene expression data

Reconstructing gene regulatory networks and transcription factor activity is crucial to understand biological processes and holds potential for developing personalized treatment. Yet, it is still an open problem as state-of-art algorithm are often not able to handle large amounts of data. Furthermore, many of the present methods predict numerous false positives and are unable to integrate other sources of information such as previously known interactions. Here we introduce KBoost, an algorithm that uses kernel PCA regression, boosting and Bayesian model averaging for fast and accurate reconstruction of gene regulatory networks. KBoost can also use a prior network built on previously known transcription factor targets. We have benchmarked KBoost using three different datasets against other high performing algorithms. The results show that our method compares favourably to other methods across datasets.

Maintained by Luis F. Iglesias-Martinez. Last updated 5 months ago.

network graphandnetwork bayesian networkinference generegulation transcriptomics systemsbiology transcription geneexpression regression principalcomponent

22.1 match 4 stars 4.60 score 9 scripts

fishr-core-team

FSA:Simple Fisheries Stock Assessment Methods

A variety of simple fish stock assessment methods.

Maintained by Derek H. Ogle. Last updated 2 months ago.

fish fisheries fisheries-management fisheries-stock-assessment population-dynamics stock-assessment

9.1 match 68 stars 11.08 score 1.7k scripts 6 dependents

easystats

datawizard:Easy Data Wrangling and Statistical Transformations

A lightweight package to assist in key steps involved in any data analysis workflow: (1) wrangling the raw data to get it in the needed form, (2) applying preprocessing steps and statistical transformations, and (3) compute statistical summaries of data properties and distributions. It is also the data wrangling backend for packages in 'easystats' ecosystem. References: Patil et al. (2022) <doi:10.21105/joss.04684>.

Maintained by Etienne Bacher. Last updated 9 days ago.

data dplyr hacktoberfest janitor manipulation reshape tidyr wrangling

6.8 match 222 stars 14.71 score 436 scripts 119 dependents

easystats

insight:Easy Access to Model Information for Various Model Objects

A tool to provide an easy, intuitive and consistent access to information contained in various R models, like model formulas, model terms, information about random effects, data that was used to fit the model or data from response variables. 'insight' mainly revolves around two types of functions: Functions that find (the names of) information, starting with 'find_', and functions that get the underlying data, starting with 'get_'. The package has a consistent syntax and works with many different model objects, where otherwise functions to access these information are missing.

Maintained by Daniel Lüdecke. Last updated 5 days ago.

easystats hacktoberfest insight models names predictors random

5.8 match 412 stars 17.24 score 568 scripts 210 dependents

dewittpe

qwraps2:Quick Wraps 2

A collection of (wrapper) functions the creator found useful for quickly placing data summaries and formatted regression results into '.Rnw' or '.Rmd' files. Functions for generating commonly used graphics, such as receiver operating curves or Bland-Altman plots, are also provided by 'qwraps2'. 'qwraps2' is a updated version of a package 'qwraps'. The original version 'qwraps' was never submitted to CRAN but can be found at <https://github.com/dewittpe/qwraps/>. The implementation and limited scope of the functions within 'qwraps2' <https://github.com/dewittpe/qwraps2/> is fundamentally different from 'qwraps'.

Maintained by Peter DeWitt. Last updated 5 months ago.

cpp

10.1 match 37 stars 9.80 score 448 scripts

chjackson

flexsurv:Flexible Parametric Survival and Multi-State Models

Flexible parametric models for time-to-event data, including the Royston-Parmar spline model, generalized gamma and generalized F distributions. Any user-defined parametric distribution can be fitted, given at least an R function defining the probability density or hazard. There are also tools for fitting and predicting from fully parametric multi-state models, based on either cause-specific hazards or mixture models.

Maintained by Christopher Jackson. Last updated 2 months ago.

cpp

7.3 match 57 stars 13.31 score 632 scripts 43 dependents

snoweye

phyclust:Phylogenetic Clustering (Phyloclustering)

Phylogenetic clustering (phyloclustering) is an evolutionary Continuous Time Markov Chain model-based approach to identify population structure from molecular data without assuming linkage equilibrium. The package phyclust (Chen 2011) provides a convenient implementation of phyloclustering for DNA and SNP data, capable of clustering individuals into subpopulations and identifying molecular sequences representative of those subpopulations. It is designed in C for performance, interfaced with R for visualization, and incorporates other popular open source programs including ms (Hudson 2002) <doi:10.1093/bioinformatics/18.2.337>, seq-gen (Rambaut and Grassly 1997) <doi:10.1093/bioinformatics/13.3.235>, Hap-Clustering (Tzeng 2005) <doi:10.1002/gepi.20063> and PAML baseml (Yang 1997, 2007) <doi:10.1093/bioinformatics/13.5.555>, <doi:10.1093/molbev/msm088>, for simulating data, additional analyses, and searching the best tree. See the phyclust website for more information, documentations and examples.

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

11.6 match 9 stars 8.45 score 126 scripts 8 dependents

mini-pw

SerolyzeR:Reading, Quality Control and Preprocessing of MBA (Multiplex Bead Assay) Data

Speeds up the process of loading raw data from MBA (Multiplex Bead Assay) examinations, performs quality control checks, and automatically normalises the data, preparing it for more advanced, downstream tasks. The main objective of the package is to create a simple environment for a user, who does not necessarily have experience with R language. The package is developed within the project 'PvSTATEM', which is an international project aiming for malaria elimination.

Maintained by Tymoteusz Kwiecinski. Last updated 16 days ago.

14.3 match 4 stars 6.68 score

mini-pw

PvSTATEM:Reading, Quality Control and Preprocessing of MBA (Multiplex Bead Assay) Data

Speeds up the process of loading raw data from MBA (Multiplex Bead Assay) examinations, performs quality control checks, and automatically normalises the data, preparing it for more advanced, downstream tasks. The main objective of the package is to create a simple environment for a user, who does not necessarily have experience with R language. The package is developed within the project of the same name - 'PvSTATEM', which is an international project aiming for malaria elimination.

Maintained by Tymoteusz Kwiecinski. Last updated 17 days ago.

14.3 match 3 stars 6.56 score 7 scripts

myaseen208

PSLM2015:Pakistan Social and Living Standards Measurement Survey 2014-15

Data and statistics of Pakistan Social and Living Standards Measurement (PSLM) survey 2014-15 from Pakistan Bureau of Statistics (<http://www.pbs.gov.pk/>).

Maintained by Muhammad Yaseen. Last updated 7 years ago.

29.9 match 3.10 score 25 scripts

arvsjo

stdReg:Regression Standardization

Contains functionality for regression standardization. Four general classes of models are allowed; generalized linear models, conditional generalized estimating equation models, Cox proportional hazards models and shared frailty gamma-Weibull models. Sjolander, A. (2016) <doi:10.1007/s10654-016-0157-3>.

Maintained by Arvid Sjolander. Last updated 4 years ago.

32.9 match 2.80 score 53 scripts 1 dependents

daroczig

logger:A Lightweight, Modern and Flexible Logging Utility

Inspired by the the 'futile.logger' R package and 'logging' Python module, this utility provides a flexible and extensible way of formatting and delivering log messages with low overhead.

Maintained by Gergely Daróczi. Last updated 2 months ago.

5.4 match 298 stars 16.88 score 1.5k scripts 98 dependents

kaz-yos

tableone:Create 'Table 1' to Describe Baseline Characteristics with or without Propensity Score Weights

Creates 'Table 1', i.e., description of baseline patient characteristics, which is essential in every medical research. Supports both continuous and categorical variables, as well as p-values and standardized mean differences. Weighted data are supported via the 'survey' package.

Maintained by Kazuki Yoshida. Last updated 3 years ago.

baseline-characteristics descriptive-statistics statistics

6.7 match 221 stars 13.55 score 2.3k scripts 12 dependents

connordonegan

surveil:Time Series Models for Disease Surveillance

Fits time trend models for routine disease surveillance tasks and returns probability distributions for a variety of quantities of interest, including age-standardized rates, period and cumulative percent change, and measures of health inequality. The models are appropriate for count data such as disease incidence and mortality data, employing a Poisson or binomial likelihood and the first-difference (random-walk) prior for unknown risk. Optionally add a covariance matrix for multiple, correlated time series models. Inference is completed using Markov chain Monte Carlo via the Stan modeling language. References: Donegan, Hughes, and Lee (2022) <doi:10.2196/34589>; Stan Development Team (2021) <https://mc-stan.org>; Theil (1972, ISBN:0-444-10378-3).

Maintained by Connor Donegan. Last updated 8 months ago.

bayesian-statistics cancer health-equity public-health rstan cpp

18.0 match 2 stars 4.98 score 12 scripts

ropensci

EML:Read and Write Ecological Metadata Language Files

Work with Ecological Metadata Language ('EML') files. 'EML' is a widely used metadata standard in the ecological and environmental sciences, described in Jones et al. (2006), <doi:10.1146/annurev.ecolsys.37.091305.110031>.

Maintained by Carl Boettiger. Last updated 3 years ago.

eml eml-metadata metadata-standard

8.0 match 97 stars 11.19 score 378 scripts 7 dependents

cran

lm.beta:Add Standardized Regression Coefficients to Linear-Model-Objects

Adds standardized regression coefficients to objects created by 'lm'. Also extends the S3 methods 'print', 'summary' and 'coef' with additional boolean argument 'standardized' and provides 'xtable'-support.

Maintained by Stefan Behrendt. Last updated 2 years ago.

14.1 match 6.31 score 612 scripts 6 dependents

hdvinod

generalCorr:Generalized Correlations, Causal Paths and Portfolio Selection

Function gmcmtx0() computes a more reliable (general) correlation matrix. Since causal paths from data are important for all sciences, the package provides many sophisticated functions. causeSummBlk() and causeSum2Blk() give easy-to-interpret causal paths. Let Z denote control variables and compare two flipped kernel regressions: X=f(Y, Z)+e1 and Y=g(X, Z)+e2. Our criterion Cr1 says that if |e1*Y|>|e2*X| then variation in X is more "exogenous or independent" than in Y, and the causal path is X to Y. Criterion Cr2 requires |e2|<|e1|. These inequalities between many absolute values are quantified by four orders of stochastic dominance. Our third criterion Cr3, for the causal path X to Y, requires new generalized partial correlations to satisfy |r*(x|y,z)|< |r*(y|x,z)|. The function parcorVec() reports generalized partials between the first variable and all others. The package provides several R functions including get0outliers() for outlier detection, bigfp() for numerical integration by the trapezoidal rule, stochdom2() for stochastic dominance, pillar3D() for 3D charts, canonRho() for generalized canonical correlations, depMeas() measures nonlinear dependence, and causeSummary(mtx) reports summary of causal paths among matrix columns. Portfolio selection: decileVote(), momentVote(), dif4mtx(), exactSdMtx() can rank several stocks. Functions whose names begin with 'boot' provide bootstrap statistical inference, including a new bootGcRsq() test for "Granger-causality" allowing nonlinear relations. A new tool for evaluation of out-of-sample portfolio performance is outOFsamp(). Panel data implementation is now included. See eight vignettes of the package for theory, examples, and usage tips. See Vinod (2019) \doi{10.1080/03610918.2015.1122048}.

Maintained by H. D. Vinod. Last updated 1 years ago.

19.8 match 2 stars 4.48 score 63 scripts 1 dependents

ips-lmu

emuR:Main Package of the EMU Speech Database Management System

Provide the EMU Speech Database Management System (EMU-SDMS) with database management, data extraction, data preparation and data visualization facilities. See <https://ips-lmu.github.io/The-EMU-SDMS-Manual/> for more details.

Maintained by Markus Jochim. Last updated 1 years ago.

12.8 match 24 stars 6.89 score 135 scripts 1 dependents

bioc

puma:Propagating Uncertainty in Microarray Analysis(including Affymetrix tranditional 3' arrays and exon arrays and Human Transcriptome Array 2.0)

Most analyses of Affymetrix GeneChip data (including tranditional 3' arrays and exon arrays and Human Transcriptome Array 2.0) are based on point estimates of expression levels and ignore the uncertainty of such estimates. By propagating uncertainty to downstream analyses we can improve results from microarray analyses. For the first time, the puma package makes a suite of uncertainty propagation methods available to a general audience. In additon to calculte gene expression from Affymetrix 3' arrays, puma also provides methods to process exon arrays and produces gene and isoform expression for alternative splicing study. puma also offers improvements in terms of scope and speed of execution over previously available uncertainty propagation methods. Included are summarisation, differential expression detection, clustering and PCA methods, together with useful plotting functions.

Maintained by Xuejun Liu. Last updated 5 months ago.

microarray onechannel preprocessing differentialexpression clustering exonarray geneexpression mrnamicroarray chiponchip alternativesplicing differentialsplicing bayesian twochannel dataimport hta2.0

18.8 match 4.53 score 17 scripts

ngreifer

WeightIt:Weighting for Covariate Balance in Observational Studies

Generates balancing weights for causal effect estimation in observational studies with binary, multi-category, or continuous point or longitudinal treatments by easing and extending the functionality of several R packages and providing in-house estimation methods. Available methods include those that rely on parametric modeling, optimization, and machine learning. Also allows for assessment of weights and checking of covariate balance by interfacing directly with the 'cobalt' package. Methods for estimating weighted regression models that take into account uncertainty in the estimation of the weights via M-estimation or bootstrapping are available. See the vignette "Installing Supporting Packages" for instructions on how to install any package 'WeightIt' uses, including those that may not be on CRAN.

Maintained by Noah Greifer. Last updated 5 days ago.

causal-inference inverse-probability-weights observational-study propensity-scores

7.3 match 112 stars 11.58 score 508 scripts 3 dependents

blue-matter

MSEtool:Management Strategy Evaluation Toolkit

Development, simulation testing, and implementation of management procedures for fisheries (see Carruthers & Hordyk (2018) <doi:10.1111/2041-210X.13081>).

Maintained by Adrian Hordyk. Last updated 26 days ago.

cpp

10.7 match 8 stars 7.69 score 163 scripts 3 dependents

lmaowisc

WR:Win Ratio Analysis of Composite Time-to-Event Outcomes

Implements various win ratio methodologies for composite endpoints of death and non-fatal events, including the (stratified) proportional win-fractions (PW) regression models (Mao and Wang, 2020 <doi:10.1111/biom.13382>), (stratified) two-sample tests with possibly recurrent nonfatal event, and sample size calculation for standard win ratio test (Mao et al., 2021 <doi:10.1111/biom.13501>).

Maintained by Lu Mao. Last updated 2 months ago.

13.4 match 6.11 score 43 scripts

rsquaredacademy

olsrr:Tools for Building OLS Regression Models

Tools designed to make it easier for users, particularly beginner/intermediate R users to build ordinary least squares regression models. Includes comprehensive regression output, heteroskedasticity tests, collinearity diagnostics, residual diagnostics, measures of influence, model fit assessment and variable selection procedures.

Maintained by Aravind Hebbali. Last updated 4 months ago.

collinearity-diagnostics linear-models regression stepwise-regression

6.7 match 103 stars 12.19 score 1.4k scripts 4 dependents

parklab

Nozzle.R1:Nozzle Reports

The Nozzle package provides an API to generate HTML reports with dynamic user interface elements based on JavaScript and CSS (Cascading Style Sheets). Nozzle was designed to facilitate summarization and rapid browsing of complex results in data analysis pipelines where multiple analyses are performed frequently on big data sets. The package can be applied to any project where user-friendly reports need to be created.

Maintained by Nils Gehlenborg. Last updated 10 years ago.

gehlenborglab html-report reproducible-research

15.3 match 68 stars 5.31 score 10 scripts 2 dependents

nutriverse

zscorer:Child Anthropometry z-Score Calculator

A tool for calculating z-scores and centiles for weight-for-age, length/height-for-age, weight-for-length/height, BMI-for-age, head circumference-for-age, age circumference-for-age, subscapular skinfold-for-age, triceps skinfold-for-age based on the WHO Child Growth Standards.

Maintained by Ernest Guevarra. Last updated 4 years ago.

anthropometric-indices anthropometry growth-charts growth-standards height-for-age nutrition weight-for-age weight-for-height z-score

11.0 match 14 stars 7.30 score 47 scripts 1 dependents

alexiosg

rugarch:Univariate GARCH Models

ARFIMA, in-mean, external regressors and various GARCH flavors, with methods for fit, forecast, simulation, inference and plotting.

Maintained by Alexios Galanos. Last updated 3 months ago.

cpp

6.6 match 26 stars 12.13 score 1.3k scripts 15 dependents

statist7

sitar:Super Imposition by Translation and Rotation Growth Curve Analysis

Functions for fitting and plotting SITAR (Super Imposition by Translation And Rotation) growth curve models. SITAR is a shape-invariant model with a regression B-spline mean curve and subject-specific random effects on both the measurement and age scales. The model was first described by Lindstrom (1995) <doi:10.1002/sim.4780141807> and developed as the SITAR method by Cole et al (2010) <doi:10.1093/ije/dyq115>.

Maintained by Tim Cole. Last updated 2 months ago.

9.2 match 13 stars 8.69 score 58 scripts 3 dependents

tidymodels

hardhat:Construct Modeling Packages

Building modeling packages is hard. A large amount of effort generally goes into providing an implementation for a new method that is efficient, fast, and correct, but often less emphasis is put on the user interface. A good interface requires specialized knowledge about S3 methods and formulas, which the average package developer might not have. The goal of 'hardhat' is to reduce the burden around building new modeling packages by providing functionality for preprocessing, predicting, and validating input.

Maintained by Hannah Frick. Last updated 1 months ago.

5.3 match 103 stars 14.88 score 175 scripts 436 dependents

wjschne

simstandard:Generate Standardized Data

Creates simulated data from structural equation models with standardized loading. Data generation methods are described in Schneider (2013) <doi:10.1177/0734282913478046>.

Maintained by W. Joel Schneider. Last updated 11 months ago.

12.8 match 6 stars 6.07 score 66 scripts 2 dependents

jeksterslab

cTMed:Continuous Time Mediation

Calculates standard errors and confidence intervals for effects in continuous-time mediation models. This package extends the work of Deboeck and Preacher (2015) <doi:10.1080/10705511.2014.973960> and Ryan and Hamaker (2021) <doi:10.1007/s11336-021-09767-0> by providing methods to generate standard errors and confidence intervals for the total, direct, and indirect effects in these models.

Maintained by Ivan Jacob Agaloos Pesigan. Last updated 20 days ago.

centrality continuous-time delta-method mediation monte-carlo-method network openblas cpp openmp

17.0 match 4.56 score 24 scripts

functionaldata

fdapace:Functional Data Analysis and Empirical Dynamics

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

Maintained by Yidong Zhou. Last updated 9 months ago.

cpp

6.7 match 31 stars 11.46 score 474 scripts 25 dependents

bpfaff

QRM:Provides R-Language Code to Examine Quantitative Risk Management Concepts

Provides functions/methods to accompany the book Quantitative Risk Management: Concepts, Techniques and Tools by Alexander J. McNeil, Ruediger Frey, and Paul Embrechts.

Maintained by Bernhard Pfaff. Last updated 5 years ago.

cpp

16.9 match 4.53 score 181 scripts 5 dependents

um-kevinhe

pprof:Modeling, Standardization and Testing for Provider Profiling

Implements linear and generalized linear models for provider profiling, incorporating both fixed and random effects. For large-scale providers, the linear profiled-based method and the SerBIN method for binary data reduce the computational burden. Provides post-modeling features, such as indirect and direct standardization measures, hypothesis testing, confidence intervals, and post-estimation visualization. For more information, see Wu et al. (2022) <doi:10.1002/sim.9387>.

Maintained by Xiaohan Liu. Last updated 5 days ago.

openblas cpp openmp

18.7 match 4.08 score 3 scripts

rvlenth

emmeans:Estimated Marginal Means, aka Least-Squares Means

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

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

4.0 match 377 stars 19.19 score 13k scripts 187 dependents

ajrgodfrey

BrailleR:Improved Access for Blind Users

Blind users do not have access to the graphical output from R without printing the content of graphics windows to an embosser of some kind. This is not as immediate as is required for efficient access to statistical output. The functions here are created so that blind people can make even better use of R. This includes the text descriptions of graphs, convenience functions to replace the functionality offered in many GUI front ends, and experimental functionality for optimising graphical content to prepare it for embossing as tactile images.

Maintained by A. Jonathan R. Godfrey. Last updated 11 months ago.

8.5 match 123 stars 8.90 score 143 scripts

adriancorrendo

metrica:Prediction Performance Metrics

A compilation of more than 80 functions designed to quantitatively and visually evaluate prediction performance of regression (continuous variables) and classification (categorical variables) of point-forecast models (e.g. APSIM, DSSAT, DNDC, supervised Machine Learning). For regression, it includes functions to generate plots (scatter, tiles, density, & Bland-Altman plot), and to estimate error metrics (e.g. MBE, MAE, RMSE), error decomposition (e.g. lack of accuracy-precision), model efficiency (e.g. NSE, E1, KGE), indices of agreement (e.g. d, RAC), goodness of fit (e.g. r, R2), adjusted correlation coefficients (e.g. CCC, dcorr), symmetric regression coefficients (intercept, slope), and mean absolute scaled error (MASE) for time series predictions. For classification (binomial and multinomial), it offers functions to generate and plot confusion matrices, and to estimate performance metrics such as accuracy, precision, recall, specificity, F-score, Cohen's Kappa, G-mean, and many more. For more details visit the vignettes <https://adriancorrendo.github.io/metrica/>.

Maintained by Adrian A. Correndo. Last updated 9 months ago.

9.1 match 77 stars 8.18 score 49 scripts

mwheymans

miceafter:Data and Statistical Analyses after Multiple Imputation

Statistical Analyses and Pooling after Multiple Imputation. A large variety of repeated statistical analysis can be performed and finally pooled. Statistical analysis that are available are, among others, Levene's test, Odds and Risk Ratios, One sample proportions, difference between proportions and linear and logistic regression models. Functions can also be used in combination with the Pipe operator. More and more statistical analyses and pooling functions will be added over time. Heymans (2007) <doi:10.1186/1471-2288-7-33>. Eekhout (2017) <doi:10.1186/s12874-017-0404-7>. Wiel (2009) <doi:10.1093/biostatistics/kxp011>. Marshall (2009) <doi:10.1186/1471-2288-9-57>. Sidi (2021) <doi:10.1080/00031305.2021.1898468>. Lott (2018) <doi:10.1080/00031305.2018.1473796>. Grund (2021) <doi:10.31234/osf.io/d459g>.

Maintained by Martijn Heymans. Last updated 2 years ago.

15.3 match 2 stars 4.84 score 23 scripts

eblondel

rsdmx:Tools for Reading SDMX Data and Metadata

Set of classes and methods to read data and metadata documents exchanged through the Statistical Data and Metadata Exchange (SDMX) framework, currently focusing on the SDMX XML standard format (SDMX-ML).

Maintained by Emmanuel Blondel. Last updated 17 days ago.

api datastructures dsd read readsdmx sdmx sdmx-format sdmx-provider sdmx-standards statistics timeseries web-services

8.0 match 105 stars 9.22 score 4 dependents

r-lib

scales:Scale Functions for Visualization

Graphical scales map data to aesthetics, and provide methods for automatically determining breaks and labels for axes and legends.

Maintained by Thomas Lin Pedersen. Last updated 5 months ago.

ggplot2

3.7 match 419 stars 19.88 score 88k scripts 7.9k dependents

bioc

DESeq2:Differential gene expression analysis based on the negative binomial distribution

Estimate variance-mean dependence in count data from high-throughput sequencing assays and test for differential expression based on a model using the negative binomial distribution.

Maintained by Michael Love. Last updated 11 days ago.

sequencing rnaseq chipseq geneexpression transcription normalization differentialexpression bayesian regression principalcomponent clustering immunooncology openblas cpp

4.6 match 375 stars 16.11 score 17k scripts 115 dependents

microsoft

wpa:Tools for Analysing and Visualising Viva Insights Data

Opinionated functions that enable easier and faster analysis of Viva Insights data. There are three main types of functions in 'wpa': (i) Standard functions create a 'ggplot' visual or a summary table based on a specific Viva Insights metric; (2) Report Generation functions generate HTML reports on a specific analysis area, e.g. Collaboration; (3) Other miscellaneous functions cover more specific applications (e.g. Subject Line text mining) of Viva Insights data. This package adheres to 'tidyverse' principles and works well with the pipe syntax. 'wpa' is built with the beginner-to-intermediate R users in mind, and is optimised for simplicity.

Maintained by Martin Chan. Last updated 4 months ago.

workplace-analytics

11.0 match 30 stars 6.69 score 39 scripts 1 dependents

lme4

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

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

Maintained by Ben Bolker. Last updated 3 days ago.

cpp

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

mkajano

HDXBoxeR:Analysis of Hydrogen-Deuterium Exchange Mass-Spectrometry Data

A protocol that facilitates the processing and analysis of Hydrogen-Deuterium Exchange Mass Spectrometry data using p-value statistics and Critical Interval analysis. It provides a pipeline for analyzing data from 'HDXExaminer' (Sierra Analytics, Trajan Scientific), automating matching and comparison of protein states through Welch's T-test and the Critical Interval statistical framework. Additionally, it simplifies data export, generates 'PyMol' scripts, and ensures calculations meet publication standards. 'HDXBoxeR' assists in various aspects of hydrogen-deuterium exchange data analysis, including reprocessing data, calculating parameters, identifying significant peptides, generating plots, and facilitating comparison between protein states. For details check papers by Hageman and Weis (2019) <doi:10.1021/acs.analchem.9b01325> and Masson et al. (2019) <doi:10.1038/s41592-019-0459-y>. 'HDXBoxeR' citation: Janowska et al. (2024) <doi:10.1093/bioinformatics/btae479>.

Maintained by Maria K. Janowska. Last updated 7 months ago.

15.8 match 2 stars 4.60 score 3 scripts

stmcg

estmeansd:Estimating the Sample Mean and Standard Deviation from Commonly Reported Quantiles in Meta-Analysis

Implements the methods of McGrath et al. (2020) <doi:10.1177/0962280219889080> and Cai et al. (2021) <doi:10.1177/09622802211047348> for estimating the sample mean and standard deviation from commonly reported quantiles in meta-analysis. These methods can be applied to studies that report the sample median, sample size, and one or both of (i) the sample minimum and maximum values and (ii) the first and third quartiles. The corresponding standard error estimators described by McGrath et al. (2023) <doi:10.1177/09622802221139233> are also included.

Maintained by Sean McGrath. Last updated 1 years ago.

15.3 match 2 stars 4.70 score 58 scripts 2 dependents

safetygraphics

safetyGraphics:Interactive Graphics for Monitoring Clinical Trial Safety

A framework for evaluation of clinical trial safety. Users can interactively explore their data using the included 'Shiny' application.

Maintained by Jeremy Wildfire. Last updated 2 years ago.

8.8 match 98 stars 8.18 score 111 scripts

plangfelder

WGCNA:Weighted Correlation Network Analysis

Functions necessary to perform Weighted Correlation Network Analysis on high-dimensional data as originally described in Horvath and Zhang (2005) <doi:10.2202/1544-6115.1128> and Langfelder and Horvath (2008) <doi:10.1186/1471-2105-9-559>. Includes functions for rudimentary data cleaning, construction of correlation networks, module identification, summarization, and relating of variables and modules to sample traits. Also includes a number of utility functions for data manipulation and visualization.

Maintained by Peter Langfelder. Last updated 6 months ago.

cpp

7.3 match 54 stars 9.65 score 5.3k scripts 32 dependents

danlwarren

ENMTools:Analysis of Niche Evolution using Niche and Distribution Models

Constructing niche models and analyzing patterns of niche evolution. Acts as an interface for many popular modeling algorithms, and allows users to conduct Monte Carlo tests to address basic questions in evolutionary ecology and biogeography. Warren, D.L., R.E. Glor, and M. Turelli (2008) <doi:10.1111/j.1558-5646.2008.00482.x> Glor, R.E., and D.L. Warren (2011) <doi:10.1111/j.1558-5646.2010.01177.x> Warren, D.L., R.E. Glor, and M. Turelli (2010) <doi:10.1111/j.1600-0587.2009.06142.x> Cardillo, M., and D.L. Warren (2016) <doi:10.1111/geb.12455> D.L. Warren, L.J. Beaumont, R. Dinnage, and J.B. Baumgartner (2019) <doi:10.1111/ecog.03900>.

Maintained by Dan Warren. Last updated 2 months ago.

10.1 match 105 stars 6.91 score 126 scripts

benmbutler

powdR:Full Pattern Summation of X-Ray Powder Diffraction Data

Full pattern summation of X-ray powder diffraction data as described in Chipera and Bish (2002) <doi:10.1107/S0021889802017405> and Butler and Hillier (2021) <doi:10.1016/j.cageo.2020.104662>. Derives quantitative estimates of crystalline and amorphous phase concentrations in complex mixtures.

Maintained by Benjamin Butler. Last updated 3 years ago.

12.6 match 12 stars 5.56 score 30 scripts

eitsupi

neopolars:R Bindings for the 'polars' Rust Library

Lightning-fast 'DataFrame' library written in 'Rust'. Convert R data to 'Polars' data and vice versa. Perform fast, lazy, larger-than-memory and optimized data queries. 'Polars' is interoperable with the package 'arrow', as both are based on the 'Apache Arrow' Columnar Format.

Maintained by Tatsuya Shima. Last updated 1 days ago.

rust cargo

14.3 match 40 stars 4.86 score 1 scripts

ksawicka

spup:Spatial Uncertainty Propagation Analysis

Uncertainty propagation analysis in spatial environmental modelling following methodology described in Heuvelink et al. (2007) <doi:10.1080/13658810601063951> and Brown and Heuvelink (2007) <doi:10.1016/j.cageo.2006.06.015>. The package provides functions for examining the uncertainty propagation starting from input data and model parameters, via the environmental model onto model outputs. The functions include uncertainty model specification, stochastic simulation and propagation of uncertainty using Monte Carlo (MC) techniques. Uncertain variables are described by probability distributions. Both numerical and categorical data types are handled. Spatial auto-correlation within an attribute and cross-correlation between attributes is accommodated for. The MC realizations may be used as input to the environmental models called from R, or externally.

Maintained by Kasia Sawicka. Last updated 1 years ago.

monte-carlo spatial uncertainty-analysis uncertainty-propagation

10.9 match 9 stars 6.31 score 57 scripts

dynverse

dyngen:A Multi-Modal Simulator for Spearheading Single-Cell Omics Analyses

A novel, multi-modal simulation engine for studying dynamic cellular processes at single-cell resolution. 'dyngen' is more flexible than current single-cell simulation engines. It allows better method development and benchmarking, thereby stimulating development and testing of novel computational methods. Cannoodt et al. (2021) <doi:10.1038/s41467-021-24152-2>.

Maintained by Robrecht Cannoodt. Last updated 2 years ago.

benchmarking single-cell single-cell-analysis single-cell-omics

9.1 match 74 stars 7.53 score 57 scripts

tobiaskley

quantspec:Quantile-Based Spectral Analysis of Time Series

Methods to determine, smooth and plot quantile periodograms for univariate and multivariate time series.

Maintained by Tobias Kley. Last updated 9 years ago.

cpp

11.7 match 10 stars 5.84 score 46 scripts 1 dependents

aphalo

photobiology:Photobiological Calculations

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

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

light photobiology quantification r4photobiology-suite radiation spectra sun-position

7.3 match 4 stars 9.35 score 604 scripts 12 dependents

sebkrantz

collapse:Advanced and Fast Data Transformation

A C/C++ based package for advanced data transformation and statistical computing in R that is extremely fast, class-agnostic, robust and programmer friendly. Core functionality includes a rich set of S3 generic grouped and weighted statistical functions for vectors, matrices and data frames, which provide efficient low-level vectorizations, OpenMP multithreading, and skip missing values by default. These are integrated with fast grouping and ordering algorithms (also callable from C), and efficient data manipulation functions. The package also provides a flexible and rigorous approach to time series and panel data in R. It further includes fast functions for common statistical procedures, detailed (grouped, weighted) summary statistics, powerful tools to work with nested data, fast data object conversions, functions for memory efficient R programming, and helpers to effectively deal with variable labels, attributes, and missing data. It is well integrated with base R classes, 'dplyr'/'tibble', 'data.table', 'sf', 'units', 'plm' (panel-series and data frames), and 'xts'/'zoo'.

Maintained by Sebastian Krantz. Last updated 6 days ago.

data-aggregation data-analysis data-manipulation data-processing data-science data-transformation econometrics high-performance panel-data scientific-computing statistics time-series weighted weights cpp openmp

4.1 match 672 stars 16.63 score 708 scripts 97 dependents

stla

syt:Young Tableaux

Deals with Young tableaux (field of combinatorics). For standard Young tabeaux, performs enumeration, counting, random generation, the Robinson-Schensted correspondence, and conversion to and from paths on the Young lattice. Also performs enumeration and counting of semistandard Young tableaux, enumeration of skew semistandard Young tableaux, enumeration of Gelfand-Tsetlin patterns, and computation of Kostka numbers.

Maintained by Stéphane Laurent. Last updated 8 months ago.

combinatorics young-tableaux

13.5 match 3 stars 5.03 score 24 scripts 1 dependents

cliffordlai

bestglm:Best Subset GLM and Regression Utilities

Best subset glm using information criteria or cross-validation, carried by using 'leaps' algorithm (Furnival and Wilson, 1974) <doi:10.2307/1267601> or complete enumeration (Morgan and Tatar, 1972) <doi:10.1080/00401706.1972.10488918>. Implements PCR and PLS using AIC/BIC. Implements one-standard deviation rule for use with the 'caret' package.

Maintained by Yuanhao Lai. Last updated 5 years ago.

12.8 match 5.29 score 418 scripts 5 dependents

timriffe

HMDHFDplus:Read Human Mortality Database and Human Fertility Database Data from the Web

Utilities for reading data from the Human Mortality Database (<https://www.mortality.org>), Human Fertility Database (<https://www.humanfertility.org>), and similar databases from the web or locally into an R session as data.frame objects. These are the two most widely used sources of demographic data to study basic demographic change, trends, and develop new demographic methods. Other supported databases at this time include the Human Fertility Collection (<https://www.fertilitydata.org>), The Japanese Mortality Database (<https://www.ipss.go.jp/p-toukei/JMD/index-en.html>), and the Canadian Human Mortality Database (<http://www.bdlc.umontreal.ca/chmd/>). Arguments and data are standardized.

Maintained by Tim Riffe. Last updated 1 months ago.

10.5 match 2 stars 6.48 score 217 scripts 10 dependents

r-gregmisc

gdata:Various R Programming Tools for Data Manipulation

Various R programming tools for data manipulation, including medical unit conversions, combining objects, character vector operations, factor manipulation, obtaining information about R objects, generating fixed-width format files, extracting components of date & time objects, operations on columns of data frames, matrix operations, operations on vectors, operations on data frames, value of last evaluated expression, and a resample() wrapper for sample() that ensures consistent behavior for both scalar and vector arguments.

Maintained by Arni Magnusson. Last updated 2 months ago.

4.9 match 9 stars 13.62 score 4.5k scripts 124 dependents

bioc

gDRutils:A package with helper functions for processing drug response data

This package contains utility functions used throughout the gDR platform to fit data, manipulate data, and convert and validate data structures. This package also has the necessary default constants for gDR platform. Many of the functions are utilized by the gDRcore package.

Maintained by Arkadiusz Gladki. Last updated 4 days ago.

software infrastructure

9.0 match 2 stars 7.40 score 3 scripts 3 dependents

ewenharrison

finalfit:Quickly Create Elegant Regression Results Tables and Plots when Modelling

Generate regression results tables and plots in final format for publication. Explore models and export directly to PDF and 'Word' using 'RMarkdown'.

Maintained by Ewen Harrison. Last updated 7 months ago.

5.8 match 270 stars 11.43 score 1.0k scripts

insightsengineering

teal.modules.clinical:'teal' Modules for Standard Clinical Outputs

Provides user-friendly tools for creating and customizing clinical trial reports. By leveraging the 'teal' framework, this package provides 'teal' modules to easily create an interactive panel that allows for seamless adjustments to data presentation, thereby streamlining the creation of detailed and accurate reports.

Maintained by Dawid Kaledkowski. Last updated 16 days ago.

clinical-trials modules nest outputs shiny

6.5 match 34 stars 10.25 score 149 scripts

elipousson

sfext:Extra Functions for Simple Feature Data

Extra functions with additional options for reading, writing, and transforming spatial data. Includes a variety of utility functions for working with tabular data with coordinates and distance and area units.

Maintained by Eli Pousson. Last updated 4 months ago.

rspatial sf

10.9 match 20 stars 6.03 score 24 scripts 5 dependents

cran

fBasics:Rmetrics - Markets and Basic Statistics

Provides a collection of functions to explore and to investigate basic properties of financial returns and related quantities. The covered fields include techniques of explorative data analysis and the investigation of distributional properties, including parameter estimation and hypothesis testing. Even more there are several utility functions for data handling and management.

Maintained by Georgi N. Boshnakov. Last updated 7 months ago.

9.2 match 2 stars 7.11 score 129 dependents

jinkim3

kim:A Toolkit for Behavioral Scientists

A collection of functions for analyzing data typically collected or used by behavioral scientists. Examples of the functions include a function that compares groups in a factorial experimental design, a function that conducts two-way analysis of variance (ANOVA), and a function that cleans a data set generated by Qualtrics surveys. Some of the functions will require installing additional package(s). Such packages and other references are cited within the section describing the relevant functions. Many functions in this package rely heavily on these two popular R packages: Dowle et al. (2021) <https://CRAN.R-project.org/package=data.table>. Wickham et al. (2021) <https://CRAN.R-project.org/package=ggplot2>.

Maintained by Jin Kim. Last updated 19 days ago.

14.0 match 7 stars 4.66 score 3 scripts

cardiomoon

interpretCI:Estimate the Confidence Interval and Interpret Step by Step

Estimate confidence intervals for mean, proportion, mean difference for unpaired and paired samples and proportion difference. Plot the confidence intervals. Generate documents explaining the statistical result step by step.

Maintained by Keon-Woong Moon. Last updated 3 years ago.

10.8 match 4 stars 6.03 score 49 scripts

skembel

picante:Integrating Phylogenies and Ecology

Functions for phylocom integration, community analyses, null-models, traits and evolution. Implements numerous ecophylogenetic approaches including measures of community phylogenetic and trait diversity, phylogenetic signal, estimation of trait values for unobserved taxa, null models for community and phylogeny randomizations, and utility functions for data input/output and phylogeny plotting. A full description of package functionality and methods are provided by Kembel et al. (2010) <doi:10.1093/bioinformatics/btq166>.

Maintained by Steven W. Kembel. Last updated 2 years ago.

5.6 match 34 stars 11.42 score 1.1k scripts 16 dependents

henrikbengtsson

matrixStats:Functions that Apply to Rows and Columns of Matrices (and to Vectors)

High-performing functions operating on rows and columns of matrices, e.g. col / rowMedians(), col / rowRanks(), and col / rowSds(). Functions optimized per data type and for subsetted calculations such that both memory usage and processing time is minimized. There are also optimized vector-based methods, e.g. binMeans(), madDiff() and weightedMedian().

Maintained by Henrik Bengtsson. Last updated 2 months ago.

matrix performance vector

3.5 match 208 stars 18.09 score 20k scripts 2.3k dependents

bioc

Biostrings:Efficient manipulation of biological strings

Memory efficient string containers, string matching algorithms, and other utilities, for fast manipulation of large biological sequences or sets of sequences.

Maintained by Hervé Pagès. Last updated 24 days ago.

sequencematching alignment sequencing genetics dataimport datarepresentation infrastructure bioconductor-package core-package

3.6 match 61 stars 17.83 score 8.6k scripts 1.2k dependents

nwaller

fungible:Psychometric Functions from the Waller Lab

Computes fungible coefficients and Monte Carlo data. Underlying theory for these functions is described in the following publications: Waller, N. (2008). Fungible Weights in Multiple Regression. Psychometrika, 73(4), 691-703, <DOI:10.1007/s11336-008-9066-z>. Waller, N. & Jones, J. (2009). Locating the Extrema of Fungible Regression Weights. Psychometrika, 74(4), 589-602, <DOI:10.1007/s11336-008-9087-7>. Waller, N. G. (2016). Fungible Correlation Matrices: A Method for Generating Nonsingular, Singular, and Improper Correlation Matrices for Monte Carlo Research. Multivariate Behavioral Research, 51(4), 554-568. Jones, J. A. & Waller, N. G. (2015). The normal-theory and asymptotic distribution-free (ADF) covariance matrix of standardized regression coefficients: theoretical extensions and finite sample behavior. Psychometrika, 80, 365-378, <DOI:10.1007/s11336-013-9380-y>. Waller, N. G. (2018). Direct Schmid-Leiman transformations and rank-deficient loadings matrices. Psychometrika, 83, 858-870. <DOI:10.1007/s11336-017-9599-0>.

Maintained by Niels Waller. Last updated 1 years ago.

12.7 match 5.01 score 136 scripts 8 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

5.0 match 15 stars 12.60 score 7.7k scripts 295 dependents

openanalytics

inTextSummaryTable:Creation of in-Text Summary Table

Creation of tables of summary statistics or counts for clinical data (for 'TLFs'). These tables can be exported as in-text table (with the 'flextable' package) for a Clinical Study Report (Word format) or a 'topline' presentation (PowerPoint format), or as interactive table (with the 'DT' package) to an html document for clinical data review.

Maintained by Laure Cougnaud. Last updated 9 months ago.

11.4 match 1 stars 5.52 score 47 scripts

ngreifer

cobalt:Covariate Balance Tables and Plots

Generate balance tables and plots for covariates of groups preprocessed through matching, weighting or subclassification, for example, using propensity scores. Includes integration with 'MatchIt', 'WeightIt', 'MatchThem', 'twang', 'Matching', 'optmatch', 'CBPS', 'ebal', 'cem', 'sbw', and 'designmatch' for assessing balance on the output of their preprocessing functions. Users can also specify data for balance assessment not generated through the above packages. Also included are methods for assessing balance in clustered or multiply imputed data sets or data sets with multi-category, continuous, or longitudinal treatments.

Maintained by Noah Greifer. Last updated 11 months ago.

causal-inference propensity-scores

4.8 match 75 stars 12.98 score 1.0k scripts 8 dependents

hredestig

crmn:CCMN and Other Normalization Methods for Metabolomics Data

Implements the Cross-contribution Compensating Multiple standard Normalization (CCMN) method described in Redestig et al. (2009) Analytical Chemistry https://doi.org/10.1021/ac901143w and other normalization algorithms.

Maintained by Henning Redestig. Last updated 5 years ago.

13.8 match 1 stars 4.56 score 24 scripts 1 dependents

ropensci

datefixR:Standardize Dates in Different Formats or with Missing Data

There are many different formats dates are commonly represented with: the order of day, month, or year can differ, different separators ("-", "/", or whitespace) can be used, months can be numerical, names, or abbreviations and year given as two digits or four. 'datefixR' takes dates in all these different formats and converts them to R's built-in date class. If 'datefixR' cannot standardize a date, such as because it is too malformed, then the user is told which date cannot be standardized and the corresponding ID for the row. 'datefixR' also allows the imputation of missing days and months with user-controlled behavior.

Maintained by Nathan Constantine-Cooke. Last updated 3 months ago.

dates wrangling cpp

8.6 match 34 stars 7.24 score 16 scripts

bioc

spiky:Spike-in calibration for cell-free MeDIP

spiky implements methods and model generation for cfMeDIP (cell-free methylated DNA immunoprecipitation) with spike-in controls. CfMeDIP is an enrichment protocol which avoids destructive conversion of scarce template, making it ideal as a "liquid biopsy," but creating certain challenges in comparing results across specimens, subjects, and experiments. The use of synthetic spike-in standard oligos allows diagnostics performed with cfMeDIP to quantitatively compare samples across subjects, experiments, and time points in both relative and absolute terms.

Maintained by Tim Triche. Last updated 5 months ago.

differentialmethylation dnamethylation normalization preprocessing qualitycontrol sequencing

12.7 match 2 stars 4.90 score 3 scripts

flr

FLa4a:A Simple and Robust Statistical Catch at Age Model

A simple and robust statistical Catch at Age model that is specifically designed for stocks with intermediate levels of data quantity and quality.

Maintained by Ernesto Jardim. Last updated 5 days ago.

9.3 match 12 stars 6.66 score 177 scripts 2 dependents

dkaschek

dMod:Dynamic Modeling and Parameter Estimation in ODE Models

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

Maintained by Daniel Kaschek. Last updated 10 days ago.

7.4 match 20 stars 8.35 score 251 scripts

florianhartig

DHARMa:Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models

The 'DHARMa' package uses a simulation-based approach to create readily interpretable scaled (quantile) residuals for fitted (generalized) linear mixed models. Currently supported are linear and generalized linear (mixed) models from 'lme4' (classes 'lmerMod', 'glmerMod'), 'glmmTMB', 'GLMMadaptive', and 'spaMM'; phylogenetic linear models from 'phylolm' (classes 'phylolm' and 'phyloglm'); generalized additive models ('gam' from 'mgcv'); 'glm' (including 'negbin' from 'MASS', but excluding quasi-distributions) and 'lm' model classes. Moreover, externally created simulations, e.g. posterior predictive simulations from Bayesian software such as 'JAGS', 'STAN', or 'BUGS' can be processed as well. The resulting residuals are standardized to values between 0 and 1 and can be interpreted as intuitively as residuals from a linear regression. The package also provides a number of plot and test functions for typical model misspecification problems, such as over/underdispersion, zero-inflation, and residual spatial, phylogenetic and temporal autocorrelation.

Maintained by Florian Hartig. Last updated 12 days ago.

glmm regression regression-diagnostics residual

4.2 match 226 stars 14.74 score 2.8k scripts 10 dependents

ggobi

GGally:Extension to 'ggplot2'

The R package 'ggplot2' is a plotting system based on the grammar of graphics. 'GGally' extends 'ggplot2' by adding several functions to reduce the complexity of combining geometric objects with transformed data. Some of these functions include a pairwise plot matrix, a two group pairwise plot matrix, a parallel coordinates plot, a survival plot, and several functions to plot networks.

Maintained by Barret Schloerke. Last updated 10 months ago.

3.8 match 597 stars 16.15 score 17k scripts 154 dependents

worldhealthorganization

anthro:Computation of the WHO Child Growth Standards

Provides WHO Child Growth Standards (z-scores) with confidence intervals and standard errors around the prevalence estimates, taking into account complex sample designs. More information on the methods is available online: <https://www.who.int/tools/child-growth-standards>.

Maintained by Dirk Schumacher. Last updated 5 months ago.

9.7 match 32 stars 6.30 score 26 scripts 2 dependents

ethan-alt

hdbayes:Bayesian Analysis of Generalized Linear Models with Historical Data

User-friendly functions for leveraging (multiple) historical data set(s) for generalized linear models. The package contains functions for sampling from the posterior distribution of a generalized linear model using the prior induced by the Bayesian hierarchical model, power prior by Ibrahim and Chen (2000) <doi:10.1214/ss/1009212673>, normalized power prior by Duan et al. (2006) <doi:10.1002/env.752>, normalized asymptotic power prior by Ibrahim et al. (2015) <doi:10.1002/sim.6728>, commensurate prior by Hobbs et al. (2011) <doi:10.1111/j.1541-0420.2011.01564.x>, robust meta-analytic-predictive prior by Schmidli et al. (2014) <doi:10.1111/biom.12242>, the latent exchangeability prior by Alt et al. (2023) <doi:10.48550/arXiv.2303.05223>, and a normal (or half-normal) prior. Functions for computing the marginal log-likelihood under each of the implemented priors are also included. The package compiles all the 'CmdStan' models once during installation using the 'instantiate' package.

Maintained by Ethan M. Alt. Last updated 6 days ago.

9.8 match 4 stars 6.23 score 7 scripts

mahshaaban

pcr:Analyzing Real-Time Quantitative PCR Data

Calculates the amplification efficiency and curves from real-time quantitative PCR (Polymerase Chain Reaction) data. Estimates the relative expression from PCR data using the double delta CT and the standard curve methods Livak & Schmittgen (2001) <doi:10.1006/meth.2001.1262>. Tests for statistical significance using two-group tests and linear regression Yuan et al. (2006) <doi: 10.1186/1471-2105-7-85>.

Maintained by Mahmoud Ahmed. Last updated 8 months ago.

data-analyses molecular-biology qpcr

8.4 match 28 stars 7.25 score 63 scripts

cran

EHR:Electronic Health Record (EHR) Data Processing and Analysis Tool

Process and analyze electronic health record (EHR) data. The 'EHR' package provides modules to perform diverse medication-related studies using data from EHR databases. Especially, the package includes modules to perform pharmacokinetic/pharmacodynamic (PK/PD) analyses using EHRs, as outlined in Choi, Beck, McNeer, Weeks, Williams, James, Niu, Abou-Khalil, Birdwell, Roden, Stein, Bejan, Denny, and Van Driest (2020) <doi:10.1002/cpt.1787>. Additional modules will be added in future. In addition, this package provides various functions useful to perform Phenome Wide Association Study (PheWAS) to explore associations between drug exposure and phenotypes obtained from EHR data, as outlined in Choi, Carroll, Beck, Mosley, Roden, Denny, and Van Driest (2018) <doi:10.1093/bioinformatics/bty306>.

Maintained by Leena Choi. Last updated 2 years ago.

16.8 match 3.60 score

ulrichriegel

Pareto:The Pareto, Piecewise Pareto and Generalized Pareto Distribution

Utilities for the Pareto, piecewise Pareto and generalized Pareto distribution that are useful for reinsurance pricing. In particular, the package provides a non-trivial algorithm that can be used to match the expected losses of a tower of reinsurance layers with a layer-independent collective risk model. The theoretical background of the matching algorithm and most other methods are described in Ulrich Riegel (2018) <doi:10.1007/s13385-018-0177-3>.

Maintained by Ulrich Riegel. Last updated 2 years ago.

8.6 match 10 stars 7.00 score 134 scripts 1 dependents

cran

Monte.Carlo.se:Monte Carlo Standard Errors

Computes Monte Carlo standard errors for summaries of Monte Carlo output. Summaries and their standard errors are based on columns of Monte Carlo simulation output. Dennis D. Boos and Jason A. Osborne (2015) <doi:10.1111/insr.12087>.

Maintained by Dennis Boos. Last updated 2 years ago.

23.1 match 2.60 score

ielbadisy

mcstatsim:Monte Carlo Statistical Simulation Tools Using a Functional Approach

A lightweight package designed to facilitate statistical simulations through functional programming. It centralizes the simulation process into a single higher-order function, enhancing manageability and usability without adding overhead from external dependencies. The package includes ready-to-use functions for common simulation targets. A detailed example can be found on <https://github.com/ielbadisy/mcstatsim>.

Maintained by Imad EL BADISY. Last updated 7 months ago.

16.9 match 1 stars 3.54 score 7 scripts

bioc

sparseMatrixStats:Summary Statistics for Rows and Columns of Sparse Matrices

High performance functions for row and column operations on sparse matrices. For example: col / rowMeans2, col / rowMedians, col / rowVars etc. Currently, the optimizations are limited to data in the column sparse format. This package is inspired by the matrixStats package by Henrik Bengtsson.

Maintained by Constantin Ahlmann-Eltze. Last updated 5 months ago.

infrastructure software datarepresentation cpp

5.0 match 54 stars 11.98 score 174 scripts 126 dependents

neuropsychology

psycho:Efficient and Publishing-Oriented Workflow for Psychological Science

The main goal of the psycho package is to provide tools for psychologists, neuropsychologists and neuroscientists, to facilitate and speed up the time spent on data analysis. It aims at supporting best practices and tools to format the output of statistical methods to directly paste them into a manuscript, ensuring statistical reporting standardization and conformity.

Maintained by Dominique Makowski. Last updated 4 years ago.

apa apa6 bayesian correlation format interpretation mixed-models neuroscience psycho psychology rstanarm statistics

5.5 match 149 stars 10.86 score 628 scripts 5 dependents

fauvernierma

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

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

Maintained by Mathieu Fauvernier. Last updated 3 months ago.

cpp

8.8 match 12 stars 6.82 score 85 scripts 1 dependents

openvolley

datavolley:Reading and Analyzing DataVolley Scout Files

Provides functions for parsing and working with volleyball match files in DataVolley format.

Maintained by Ben Raymond. Last updated 2 months ago.

openvolley sports-analytics volleyball

7.1 match 31 stars 8.31 score 94 scripts 11 dependents

sfcheung

semfindr:Influential Cases in Structural Equation Modeling

Sensitivity analysis in structural equation modeling using influence measures and diagnostic plots. Support leave-one-out casewise sensitivity analysis presented by Pek and MacCallum (2011) <doi:10.1080/00273171.2011.561068> and approximate casewise influence using scores and casewise likelihood.

Maintained by Shu Fai Cheung. Last updated 13 days ago.

diagnostics influential-cases lavaan outlier-detection sensitivity-analysis structural-equation-modeling

9.8 match 1 stars 6.03 score 90 scripts

motherhack3r

mitre:Cybersecurity MITRE Standards Data and Digraphs

Extract, transform and load MITRE standards. This package gives you an approach to cybersecurity data sets. All data sets are build on runtime downloading raw data from MITRE public services. MITRE <https://www.mitre.org/> is a government-funded research organization based in Bedford and McLean. Current version includes most used standards as data frames. It also provide a list of nodes and edges with all relationships.

Maintained by Humbert Costas. Last updated 4 years ago.

data-driven-security mitre mitre-shield

11.9 match 19 stars 4.98 score 6 scripts

pauljohn32

rockchalk:Regression Estimation and Presentation

A collection of functions for interpretation and presentation of regression analysis. These functions are used to produce the statistics lectures in <https://pj.freefaculty.org/guides/>. Includes regression diagnostics, regression tables, and plots of interactions and "moderator" variables. The emphasis is on "mean-centered" and "residual-centered" predictors. The vignette 'rockchalk' offers a fairly comprehensive overview. The vignette 'Rstyle' has advice about coding in R. The package title 'rockchalk' refers to our school motto, 'Rock Chalk Jayhawk, Go K.U.'.

Maintained by Paul E. Johnson. Last updated 3 years ago.

8.3 match 7.13 score 584 scripts 18 dependents

cran

MASS:Support Functions and Datasets for Venables and Ripley's MASS

Functions and datasets to support Venables and Ripley, "Modern Applied Statistics with S" (4th edition, 2002).

Maintained by Brian Ripley. Last updated 16 days ago.

5.5 match 19 stars 10.53 score 11k dependents

finnishcancerregistry

popEpi:Functions for Epidemiological Analysis using Population Data

Enables computation of epidemiological statistics, including those where counts or mortality rates of the reference population are used. Currently supported: excess hazard models (Dickman, Sloggett, Hills, and Hakulinen (2012) <doi:10.1002/sim.1597>), rates, mean survival times, relative/net survival (in particular the Ederer II (Ederer and Heise (1959)) and Pohar Perme (Pohar Perme, Stare, and Esteve (2012) <doi:10.1111/j.1541-0420.2011.01640.x>) estimators), and standardized incidence and mortality ratios, all of which can be easily adjusted for by covariates such as age. Fast splitting and aggregation of 'Lexis' objects (from package 'Epi') and other computations achieved using 'data.table'.

Maintained by Joonas Miettinen. Last updated 1 months ago.

adjust-estimates age-adjusting direct-adjusting epidemiology indirect-adjusting survival

7.3 match 8 stars 8.05 score 117 scripts 1 dependents

muschellij2

fslr:Wrapper Functions for 'FSL' ('FMRIB' Software Library) from Functional MRI of the Brain ('FMRIB')

Wrapper functions that interface with 'FSL' <http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/>, a powerful and commonly-used 'neuroimaging' software, using system commands. The goal is to be able to interface with 'FSL' completely in R, where you pass R objects of class 'nifti', implemented by package 'oro.nifti', and the function executes an 'FSL' command and returns an R object of class 'nifti' if desired.

Maintained by John Muschelli. Last updated 1 months ago.

fsl fslr neuroimaging neuroimaging-analysis neuroimaging-data-science

7.3 match 41 stars 8.01 score 420 scripts

bioc

MatrixGenerics:S4 Generic Summary Statistic Functions that Operate on Matrix-Like Objects

S4 generic functions modeled after the 'matrixStats' API for alternative matrix implementations. Packages with alternative matrix implementation can depend on this package and implement the generic functions that are defined here for a useful set of row and column summary statistics. Other package developers can import this package and handle a different matrix implementations without worrying about incompatibilities.

Maintained by Peter Hickey. Last updated 2 months ago.

infrastructure software bioconductor-package core-package

5.0 match 12 stars 11.64 score 129 scripts 1.3k dependents

sbegueria

SPEI:Calculation of the Standardized Precipitation-Evapotranspiration Index

A set of functions for computing potential evapotranspiration and several widely used drought indices including the Standardized Precipitation-Evapotranspiration Index (SPEI).

Maintained by Santiago Beguería. Last updated 2 years ago.

6.2 match 82 stars 9.27 score 314 scripts 20 dependents

openanalytics

clinUtils:General Utility Functions for Analysis of Clinical Data

Utility functions to facilitate the import, the reporting and analysis of clinical data. Example datasets in 'SDTM' and 'ADaM' format, containing a subset of patients/domains from the 'CDISC Pilot 01 study' are also available as R datasets to demonstrate the package functionalities.

Maintained by Laure Cougnaud. Last updated 10 months ago.

8.5 match 3 stars 6.78 score 105 scripts 3 dependents

geanders

weathermetrics:Functions to Convert Between Weather Metrics

Functions to convert between weather metrics, including conversions for metrics of temperature, air moisture, wind speed, and precipitation. This package also includes functions to calculate the heat index from air temperature and air moisture.

Maintained by Brooke Anderson. Last updated 8 years ago.

6.9 match 23 stars 8.32 score 506 scripts 1 dependents

kenithgrey

ggQC:Quality Control Charts for 'ggplot'

Plot single and faceted type quality control charts for 'ggplot'.

Maintained by Kenith Grey. Last updated 6 years ago.

ggplot2 qcc quality-control xmr

8.6 match 46 stars 6.74 score 119 scripts

bioc

MetaboCoreUtils:Core Utils for Metabolomics Data

MetaboCoreUtils defines metabolomics-related core functionality provided as low-level functions to allow a data structure-independent usage across various R packages. This includes functions to calculate between ion (adduct) and compound mass-to-charge ratios and masses or functions to work with chemical formulas. The package provides also a set of adduct definitions and information on some commercially available internal standard mixes commonly used in MS experiments.

Maintained by Johannes Rainer. Last updated 5 months ago.

infrastructure metabolomics massspectrometry mass-spectrometry

6.1 match 9 stars 9.40 score 58 scripts 36 dependents

cbailiss

pivottabler:Create Pivot Tables

Create regular pivot tables with just a few lines of R. More complex pivot tables can also be created, e.g. pivot tables with irregular layouts, multiple calculations and/or derived calculations based on multiple data frames. Pivot tables are constructed using R only and can be written to a range of output formats (plain text, 'HTML', 'Latex' and 'Excel'), including with styling/formatting.

Maintained by Christopher Bailiss. Last updated 1 years ago.

calculations html htmlwidget latex pivot-tables visualization

7.1 match 122 stars 8.08 score 358 scripts 1 dependents

wviechtb

metafor:Meta-Analysis Package for R

A comprehensive collection of functions for conducting meta-analyses in R. The package includes functions to calculate various effect sizes or outcome measures, fit equal-, fixed-, random-, and mixed-effects models to such data, carry out moderator and meta-regression analyses, and create various types of meta-analytical plots (e.g., forest, funnel, radial, L'Abbe, Baujat, bubble, and GOSH plots). For meta-analyses of binomial and person-time data, the package also provides functions that implement specialized methods, including the Mantel-Haenszel method, Peto's method, and a variety of suitable generalized linear (mixed-effects) models (i.e., mixed-effects logistic and Poisson regression models). Finally, the package provides functionality for fitting meta-analytic multivariate/multilevel models that account for non-independent sampling errors and/or true effects (e.g., due to the inclusion of multiple treatment studies, multiple endpoints, or other forms of clustering). Network meta-analyses and meta-analyses accounting for known correlation structures (e.g., due to phylogenetic relatedness) can also be conducted. An introduction to the package can be found in Viechtbauer (2010) <doi:10.18637/jss.v036.i03>.

Maintained by Wolfgang Viechtbauer. Last updated 1 days ago.

meta-analysis mixed-effects multilevel-models multivariate

3.5 match 246 stars 16.30 score 4.9k scripts 92 dependents

opengeos

whitebox:'WhiteboxTools' R Frontend

An R frontend for the 'WhiteboxTools' library, which is an advanced geospatial data analysis platform developed by Prof. John Lindsay at the University of Guelph's Geomorphometry and Hydrogeomatics Research Group. 'WhiteboxTools' can be used to perform common geographical information systems (GIS) analysis operations, such as cost-distance analysis, distance buffering, and raster reclassification. Remote sensing and image processing tasks include image enhancement (e.g. panchromatic sharpening, contrast adjustments), image mosaicing, numerous filtering operations, simple classification (k-means), and common image transformations. 'WhiteboxTools' also contains advanced tooling for spatial hydrological analysis (e.g. flow-accumulation, watershed delineation, stream network analysis, sink removal), terrain analysis (e.g. common terrain indices such as slope, curvatures, wetness index, hillshading; hypsometric analysis; multi-scale topographic position analysis), and LiDAR data processing. Suggested citation: Lindsay (2016) <doi:10.1016/j.cageo.2016.07.003>.

Maintained by Andrew Brown. Last updated 5 months ago.

geomorphometry geoprocessing geospatial gis hydrology remote-sensing rstudio

5.9 match 173 stars 9.65 score 203 scripts 2 dependents

arcaldwell49

Superpower:Simulation-Based Power Analysis for Factorial Designs

Functions to perform simulations of ANOVA designs of up to three factors. Calculates the observed power and average observed effect size for all main effects and interactions in the ANOVA, and all simple comparisons between conditions. Includes functions for analytic power calculations and additional helper functions that compute effect sizes for ANOVA designs, observed error rates in the simulations, and functions to plot power curves. Please see Lakens, D., & Caldwell, A. R. (2021). "Simulation-Based Power Analysis for Factorial Analysis of Variance Designs". <doi:10.1177/2515245920951503>.

Maintained by Aaron Caldwell. Last updated 3 months ago.

6.3 match 66 stars 9.02 score 106 scripts 1 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 16 days ago.

genetics imputation lmm fortran

4.8 match 12 stars 11.88 score 448 scripts 16 dependents

sciviews

svDialogs:'SciViews' - Standard Dialog Boxes for Windows, MacOS and Linuxes

Quickly construct standard dialog boxes for your GUI, including message boxes, input boxes, list, file or directory selection, ... In case R cannot display GUI dialog boxes, a simpler command line version of these interactive elements is also provided as fallback solution.

Maintained by Philippe Grosjean. Last updated 3 years ago.

dialog-box gui sciviews

6.4 match 8 stars 8.85 score 289 scripts 12 dependents

mamaz7

AICcmodavg:Model Selection and Multimodel Inference Based on (Q)AIC(c)

Functions to implement model selection and multimodel inference based on Akaike's information criterion (AIC) and the second-order AIC (AICc), as well as their quasi-likelihood counterparts (QAIC, QAICc) from various model object classes. The package implements classic model averaging for a given parameter of interest or predicted values, as well as a shrinkage version of model averaging parameter estimates or effect sizes. The package includes diagnostics and goodness-of-fit statistics for certain model types including those of 'unmarkedFit' classes estimating demographic parameters after accounting for imperfect detection probabilities. Some functions also allow the creation of model selection tables for Bayesian models of the 'bugs', 'rjags', and 'jagsUI' classes. Functions also implement model selection using BIC. Objects following model selection and multimodel inference can be formatted to LaTeX using 'xtable' methods included in the package.

Maintained by Marc J. Mazerolle. Last updated 10 days ago.

7.2 match 1 stars 7.83 score 1.8k scripts 8 dependents

ropensci

tracerer:Tracer from R

'BEAST2' (<https://www.beast2.org>) is a widely used Bayesian phylogenetic tool, that uses DNA/RNA/protein data and many model priors to create a posterior of jointly estimated phylogenies and parameters. 'Tracer' (<https://github.com/beast-dev/tracer/>) is a GUI tool to parse and analyze the files generated by 'BEAST2'. This package provides a way to parse and analyze 'BEAST2' input files without active user input, but using R function calls instead.

Maintained by Richèl J.C. Bilderbeek. Last updated 1 years ago.

cpp

8.7 match 8 stars 6.49 score 86 scripts 3 dependents

nacnudus

tidyxl:Read Untidy Excel Files

Imports non-tabular from Excel files into R. Exposes cell content, position and formatting in a tidy structure for further manipulation. Tokenizes Excel formulas. Supports '.xlsx' and '.xlsm' via the embedded 'RapidXML' C++ library <https://rapidxml.sourceforge.net>. Does not support '.xlsb' or '.xls'.

Maintained by Duncan Garmonsway. Last updated 1 years ago.

excelreader rcpp spreadsheet tidy cpp

5.3 match 251 stars 10.69 score 382 scripts 13 dependents

pharmaverse

admiralophtha:ADaM in R Asset Library - Ophthalmology

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

Maintained by Edoardo Mancini. Last updated 2 months ago.

7.0 match 15 stars 7.94 score 10 scripts

tidymodels

infer:Tidy Statistical Inference

The objective of this package is to perform inference using an expressive statistical grammar that coheres with the tidy design framework.

Maintained by Simon Couch. Last updated 6 months ago.

3.5 match 734 stars 15.69 score 3.5k scripts 17 dependents

veronica0206

nlpsem:Linear and Nonlinear Longitudinal Process in Structural Equation Modeling Framework

Provides computational tools for nonlinear longitudinal models, in particular the intrinsically nonlinear models, in four scenarios: (1) univariate longitudinal processes with growth factors, with or without covariates including time-invariant covariates (TICs) and time-varying covariates (TVCs); (2) multivariate longitudinal processes that facilitate the assessment of correlation or causation between multiple longitudinal variables; (3) multiple-group models for scenarios (1) and (2) to evaluate differences among manifested groups, and (4) longitudinal mixture models for scenarios (1) and (2), with an assumption that trajectories are from multiple latent classes. The methods implemented are introduced in Jin Liu (2023) <arXiv:2302.03237v2>.

Maintained by Jin Liu. Last updated 4 months ago.

8.0 match 145 stars 6.91 score 16 scripts

hemingnm

SESraster:Raster Randomization for Null Hypothesis Testing

Randomization of presence/absence species distribution raster data with or without including spatial structure for calculating standardized effect sizes and testing null hypothesis. The randomization algorithms are based on classical algorithms for matrices (Gotelli 2000, <doi:10.2307/177478>) implemented for raster data.

Maintained by Neander Marcel Heming. Last updated 5 months ago.

null-models randomization raster spatial spatial-analysis species-distribution-modelling

8.3 match 7 stars 6.61 score 32 scripts 2 dependents

ropensci

occCite:Querying and Managing Large Biodiversity Occurrence Datasets

Facilitates the gathering of biodiversity occurrence data from disparate sources. Metadata is managed throughout the process to facilitate reporting and enhanced ability to repeat analyses.

Maintained by Hannah L. Owens. Last updated 5 months ago.

biodiversity-data biodiversity-informatics biodiversity-standards citations museum-collection-specimens museum-collections museum-metadata

7.5 match 23 stars 7.30 score 43 scripts

novartis

xgxr:Exploratory Graphics for Pharmacometrics

Supports a structured approach for exploring PKPD data <https://opensource.nibr.com/xgx/>. It also contains helper functions for enabling the modeler to follow best R practices (by appending the program name, figure name location, and draft status to each plot). In addition, it enables the modeler to follow best graphical practices (by providing a theme that reduces chart ink, and by providing time-scale, log-scale, and reverse-log-transform-scale functions for more readable axes). Finally, it provides some data checking and summarizing functions for rapidly exploring pharmacokinetics and pharmacodynamics (PKPD) datasets.

Maintained by Andrew Stein. Last updated 1 years ago.

7.0 match 13 stars 7.76 score 105 scripts 5 dependents

lbbe-software

fitdistrplus:Help to Fit of a Parametric Distribution to Non-Censored or Censored Data

Extends the fitdistr() function (of the MASS package) with several functions to help the fit of a parametric distribution to non-censored or censored data. Censored data may contain left censored, right censored and interval censored values, with several lower and upper bounds. In addition to maximum likelihood estimation (MLE), the package provides moment matching (MME), quantile matching (QME), maximum goodness-of-fit estimation (MGE) and maximum spacing estimation (MSE) methods (available only for non-censored data). Weighted versions of MLE, MME, QME and MSE are available. See e.g. Casella & Berger (2002), Statistical inference, Pacific Grove, for a general introduction to parametric estimation.

Maintained by Aurélie Siberchicot. Last updated 12 days ago.

3.4 match 54 stars 16.15 score 4.5k scripts 153 dependents

r-lidar

lidR:Airborne LiDAR Data Manipulation and Visualization for Forestry Applications

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

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

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

3.8 match 623 stars 14.47 score 844 scripts 8 dependents

r-forge

survey:Analysis of Complex Survey Samples

Summary statistics, two-sample tests, rank tests, generalised linear models, cumulative link models, Cox models, loglinear models, and general maximum pseudolikelihood estimation for multistage stratified, cluster-sampled, unequally weighted survey samples. Variances by Taylor series linearisation or replicate weights. Post-stratification, calibration, and raking. Two-phase and multiphase subsampling designs. Graphics. PPS sampling without replacement. Small-area estimation. Dual-frame designs.

Maintained by "Thomas Lumley". Last updated 6 months ago.

cpp

3.9 match 1 stars 13.94 score 13k scripts 232 dependents

jmgirard

circumplex:Analysis and Visualization of Circular Data

Circumplex models, which organize constructs in a circle around two underlying dimensions, are popular for studying interpersonal functioning, mood/affect, and vocational preferences/environments. This package provides tools for analyzing and visualizing circular data, including scoring functions for relevant instruments and a generalization of the bootstrapped structural summary method from Zimmermann & Wright (2017) <doi:10.1177/1073191115621795> and functions for creating publication-ready tables and figures from the results.

Maintained by Jeffrey Girard. Last updated 5 months ago.

circular circumplex data-analysis ggplot2 interpersonal psychology rcpparmadillo tidyverse openblas cpp openmp

8.3 match 11 stars 6.54 score 52 scripts

egenn

rtemis:Machine Learning and Visualization

Advanced Machine Learning and Visualization. Unsupervised Learning (Clustering, Decomposition), Supervised Learning (Classification, Regression), Cross-Decomposition, Bagging, Boosting, Meta-models. Static and interactive graphics.

Maintained by E.D. Gennatas. Last updated 1 months ago.

data-science data-visualization machine-learning machine-learning-library visualization

7.5 match 145 stars 7.09 score 50 scripts 2 dependents

rstudio

bigD:Flexibly Format Dates and Times to a Given Locale

Format dates and times flexibly and to whichever locales make sense. Parses dates, times, and date-times in various formats (including string-based ISO 8601 constructions). The formatting syntax gives the user many options for formatting the date and time output in a precise manner. Time zones in the input can be expressed in multiple ways and there are many options for formatting time zones in the output as well. Several of the provided helper functions allow for automatic generation of locale-aware formatting patterns based on date/time skeleton formats and standardized date/time formats with varying specificity.

Maintained by Richard Iannone. Last updated 12 days ago.

date datetime easy-to-use i18n time

5.7 match 19 stars 9.46 score 1 scripts 112 dependents

pharmaverse

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

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

Maintained by Stefan Bundfuss. Last updated 2 months ago.

6.1 match 32 stars 8.66 score 30 scripts

sthawinke

oosse:Out-of-Sample R² with Standard Error Estimation

Estimates out-of-sample R² through bootstrap or cross-validation as a measure of predictive performance. In addition, a standard error for this point estimate is provided, and confidence intervals are constructed.

Maintained by Stijn Hawinkel. Last updated 6 months ago.

12.3 match 4 stars 4.30 score 5 scripts

ropensci

outcomerate:AAPOR Survey Outcome Rates

Standardized survey outcome rate functions, including the response rate, contact rate, cooperation rate, and refusal rate. These outcome rates allow survey researchers to measure the quality of survey data using definitions published by the American Association of Public Opinion Research (AAPOR). For details on these standards, see AAPOR (2016) <https://www.aapor.org/Standards-Ethics/Standard-Definitions-(1).aspx>.

Maintained by Rafael Pilliard Hellwig. Last updated 4 years ago.

aapor disposition-codes peer-reviewed standards survey

11.0 match 5 stars 4.78 score 24 scripts

r-forge

surveillance:Temporal and Spatio-Temporal Modeling and Monitoring of Epidemic Phenomena

Statistical methods for the modeling and monitoring of time series of counts, proportions and categorical data, as well as for the modeling of continuous-time point processes of epidemic phenomena. The monitoring methods focus on aberration detection in count data time series from public health surveillance of communicable diseases, but applications could just as well originate from environmetrics, reliability engineering, econometrics, or social sciences. The package implements many typical outbreak detection procedures such as the (improved) Farrington algorithm, or the negative binomial GLR-CUSUM method of Hoehle and Paul (2008) <doi:10.1016/j.csda.2008.02.015>. A novel CUSUM approach combining logistic and multinomial logistic modeling is also included. The package contains several real-world data sets, the ability to simulate outbreak data, and to visualize the results of the monitoring in a temporal, spatial or spatio-temporal fashion. A recent overview of the available monitoring procedures is given by Salmon et al. (2016) <doi:10.18637/jss.v070.i10>. For the retrospective analysis of epidemic spread, the package provides three endemic-epidemic modeling frameworks with tools for visualization, likelihood inference, and simulation. hhh4() estimates models for (multivariate) count time series following Paul and Held (2011) <doi:10.1002/sim.4177> and Meyer and Held (2014) <doi:10.1214/14-AOAS743>. twinSIR() models the susceptible-infectious-recovered (SIR) event history of a fixed population, e.g, epidemics across farms or networks, as a multivariate point process as proposed by Hoehle (2009) <doi:10.1002/bimj.200900050>. twinstim() estimates self-exciting point process models for a spatio-temporal point pattern of infective events, e.g., time-stamped geo-referenced surveillance data, as proposed by Meyer et al. (2012) <doi:10.1111/j.1541-0420.2011.01684.x>. A recent overview of the implemented space-time modeling frameworks for epidemic phenomena is given by Meyer et al. (2017) <doi:10.18637/jss.v077.i11>.

Maintained by Sebastian Meyer. Last updated 2 days ago.

cpp

4.9 match 2 stars 10.68 score 446 scripts 3 dependents

sbgraves237

Ecdat:Data Sets for Econometrics

Data sets for econometrics, including political science.

Maintained by Spencer Graves. Last updated 4 months ago.

7.2 match 2 stars 7.25 score 740 scripts 3 dependents

xfim

ggmcmc:Tools for Analyzing MCMC Simulations from Bayesian Inference

Tools for assessing and diagnosing convergence of Markov Chain Monte Carlo simulations, as well as for graphically display results from full MCMC analysis. The package also facilitates the graphical interpretation of models by providing flexible functions to plot the results against observed variables, and functions to work with hierarchical/multilevel batches of parameters (Fernández-i-Marín, 2016 <doi:10.18637/jss.v070.i09>).

Maintained by Xavier Fernández i Marín. Last updated 2 years ago.

bayesian-data-analysis ggplot2 graphical jags mcmc stan

4.3 match 112 stars 12.02 score 1.6k scripts 8 dependents

flrd

standardlastprofile:Data Package for BDEW Standard Load Profiles in Electricity

Data on standard load profiles from the German Association of Energy and Water Industries (BDEW Bundesverband der Energie- und Wasserwirtschaft e.V.) in a tidy format. The data and methodology are described in VDEW (1999), "Repräsentative VDEW-Lastprofile", <https://www.bdew.de/media/documents/1999_Repraesentative-VDEW-Lastprofile.pdf>. The package also offers an interface for generating a standard load profile over a user-defined period. For the algorithm, see VDEW (2000), "Anwendung der Repräsentativen VDEW-Lastprofile step-by-step", <https://www.bdew.de/media/documents/2000131_Anwendung-repraesentativen_Lastprofile-Step-by-step.pdf>.

Maintained by Markus Döring. Last updated 8 months ago.

data electricity germany

13.9 match 1 stars 3.70 score 4 scripts

r-forge

car:Companion to Applied Regression

Functions to Accompany J. Fox and S. Weisberg, An R Companion to Applied Regression, Third Edition, Sage, 2019.

Maintained by John Fox. Last updated 5 months ago.

3.4 match 15.29 score 43k scripts 901 dependents

r-forge

sandwich:Robust Covariance Matrix Estimators

Object-oriented software for model-robust covariance matrix estimators. Starting out from the basic robust Eicker-Huber-White sandwich covariance methods include: heteroscedasticity-consistent (HC) covariances for cross-section data; heteroscedasticity- and autocorrelation-consistent (HAC) covariances for time series data (such as Andrews' kernel HAC, Newey-West, and WEAVE estimators); clustered covariances (one-way and multi-way); panel and panel-corrected covariances; outer-product-of-gradients covariances; and (clustered) bootstrap covariances. All methods are applicable to (generalized) linear model objects fitted by lm() and glm() but can also be adapted to other classes through S3 methods. Details can be found in Zeileis et al. (2020) <doi:10.18637/jss.v095.i01>, Zeileis (2004) <doi:10.18637/jss.v011.i10> and Zeileis (2006) <doi:10.18637/jss.v016.i09>.

Maintained by Achim Zeileis. Last updated 2 months ago.

3.4 match 14.92 score 11k scripts 887 dependents

alexanderrobitzsch

miceadds:Some Additional Multiple Imputation Functions, Especially for 'mice'

Contains functions for multiple imputation which complements existing functionality in R. In particular, several imputation methods for the mice package (van Buuren & Groothuis-Oudshoorn, 2011, <doi:10.18637/jss.v045.i03>) are implemented. Main features of the miceadds package include plausible value imputation (Mislevy, 1991, <doi:10.1007/BF02294457>), multilevel imputation for variables at any level or with any number of hierarchical and non-hierarchical levels (Grund, Luedtke & Robitzsch, 2018, <doi:10.1177/1094428117703686>; van Buuren, 2018, Ch.7, <doi:10.1201/9780429492259>), imputation using partial least squares (PLS) for high dimensional predictors (Robitzsch, Pham & Yanagida, 2016), nested multiple imputation (Rubin, 2003, <doi:10.1111/1467-9574.00217>), substantive model compatible imputation (Bartlett et al., 2015, <doi:10.1177/0962280214521348>), and features for the generation of synthetic datasets (Reiter, 2005, <doi:10.1111/j.1467-985X.2004.00343.x>; Nowok, Raab, & Dibben, 2016, <doi:10.18637/jss.v074.i11>).

Maintained by Alexander Robitzsch. Last updated 16 days ago.

missing-data multiple-imputation openblas cpp

5.6 match 16 stars 9.16 score 542 scripts 9 dependents

hwborchers

pracma:Practical Numerical Math Functions

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

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

4.1 match 29 stars 12.34 score 6.6k scripts 931 dependents

nicwir

QurvE:Robust and User-Friendly Analysis of Growth and Fluorescence Curves

High-throughput analysis of growth curves and fluorescence data using three methods: linear regression, growth model fitting, and smooth spline fit. Analysis of dose-response relationships via smoothing splines or dose-response models. Complete data analysis workflows can be executed in a single step via user-friendly wrapper functions. The results of these workflows are summarized in detailed reports as well as intuitively navigable 'R' data containers. A 'shiny' application provides access to all features without requiring any programming knowledge. The package is described in further detail in Wirth et al. (2023) <doi:10.1038/s41596-023-00850-7>.

Maintained by Nicolas T. Wirth. Last updated 1 years ago.

8.3 match 25 stars 6.00 score 7 scripts

gabferreira

phyloraster:Evolutionary Diversity Metrics for Raster Data

Phylogenetic Diversity (PD, Faith 1992), Evolutionary Distinctiveness (ED, Isaac et al. 2007), Phylogenetic Endemism (PE, Rosauer et al. 2009; Laffan et al. 2016), and Weighted Endemism (WE, Laffan et al. 2016) for presence-absence raster. Faith, D. P. (1992) <doi:10.1016/0006-3207(92)91201-3> Isaac, N. J. et al. (2007) <doi:10.1371/journal.pone.0000296> Laffan, S. W. et al. (2016) <doi:10.1111/2041-210X.12513> Rosauer, D. et al. (2009) <doi:10.1111/j.1365-294X.2009.04311.x>.

Maintained by Gabriela Alves-Ferreira. Last updated 16 days ago.

8.8 match 7 stars 5.66 score 33 scripts

alistaire47

passport:Travel Smoothly Between Country Name and Code Formats

Smooths the process of working with country names and codes via powerful parsing, standardization, and conversion utilities arranged in a simple, consistent API. Country name formats include multiple sources including the Unicode Common Locale Data Repository (CLDR, <http://cldr.unicode.org/>) common-sense standardized names in hundreds of languages.

Maintained by Edward Visel. Last updated 4 years ago.

country-codes country-data country-names

8.1 match 35 stars 6.17 score 28 scripts 1 dependents

aalfons

robustHD:Robust Methods for High-Dimensional Data

Robust methods for high-dimensional data, in particular linear model selection techniques based on least angle regression and sparse regression. Specifically, the package implements robust least angle regression (Khan, Van Aelst & Zamar, 2007; <doi:10.1198/016214507000000950>), (robust) groupwise least angle regression (Alfons, Croux & Gelper, 2016; <doi:10.1016/j.csda.2015.02.007>), and sparse least trimmed squares regression (Alfons, Croux & Gelper, 2013; <doi:10.1214/12-AOAS575>).

Maintained by Andreas Alfons. Last updated 9 months ago.

openblas cpp openmp

7.0 match 10 stars 7.06 score 174 scripts 8 dependents

bioc

DEGreport:Report of DEG analysis

Creation of ready-to-share figures of differential expression analyses of count data. It integrates some of the code mentioned in DESeq2 and edgeR vignettes, and report a ranked list of genes according to the fold changes mean and variability for each selected gene.

Maintained by Lorena Pantano. Last updated 5 months ago.

differentialexpression visualization rnaseq reportwriting geneexpression immunooncology bioconductor differential-expression qc report rna-seq smallrna

5.2 match 24 stars 9.42 score 354 scripts 1 dependents

kolesarm

dfadjust:Degrees of Freedom Adjustment for Robust Standard Errors

Computes small-sample degrees of freedom adjustment for heteroskedasticity robust standard errors, and for clustered standard errors in linear regression. See Imbens and Kolesár (2016) <doi:10.1162/REST_a_00552> for a discussion of these adjustments.

Maintained by Michal Kolesár. Last updated 3 months ago.

8.5 match 31 stars 5.75 score 12 scripts

insightsengineering

chevron:Standard TLGs for Clinical Trials Reporting

Provide standard tables, listings, and graphs (TLGs) libraries used in clinical trials. This package implements a structure to reformat the data with 'dunlin', create reporting tables using 'rtables' and 'tern' with standardized input arguments to enable quick generation of standard outputs. In addition, it also provides comprehensive data checks and script generation functionality.

Maintained by Joe Zhu. Last updated 24 days ago.

clinical-trials graphs listings nest reporting tables

5.9 match 12 stars 8.24 score 12 scripts

kjhealy

gssrdoc:Document General Social Survey Variable

The General Social Survey (GSS) is a long-running, mostly annual survey of US households. It is administered by the National Opinion Research Center (NORC). This package contains the a tibble with information on the survey variables, together with every variable documented as an R help page. For more information on the GSS see \url{http://gss.norc.org}.

Maintained by Kieran Healy. Last updated 11 months ago.

21.4 match 2.28 score 38 scripts

lisalibungan

shapeR:Collection and Analysis of Otolith Shape Data

Studies otolith shape variation among fish populations. Otoliths are calcified structures found in the inner ear of teleost fish and their shape has been known to vary among several fish populations and stocks, making them very useful in taxonomy, species identification and to study geographic variations. The package extends previously described software used for otolith shape analysis by allowing the user to automatically extract closed contour outlines from a large number of images, perform smoothing to eliminate pixel noise, choose from conducting either a Fourier or wavelet transform to the outlines and visualize the mean shape. The output of the package are independent Fourier or wavelet coefficients which can be directly imported into a wide range of statistical packages in R. The package might prove useful in studies of any two dimensional objects.

Maintained by Lisa Anne Libungan. Last updated 7 years ago.

11.0 match 9 stars 4.45 score 21 scripts