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"name": "R-gigg",
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{
"name": "R-GIGrvg",
"description": "Random variate generator for the GIG distribution"
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{
"name": "R-gimme",
"description": "Group Iterative Multiple Model Estimation"
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{
"name": "R-gimmeTools",
"description": "Supplemental tools for R-gimme"
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{
"name": "R-Gini",
"description": "Various equations to calculate Gini coefficients"
},
{
"name": "R-ginormal",
"description": "Generalized inverse normal distribution density and generation"
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{
"name": "R-GiRaF",
"description": "Gibbs Random Fields Analysis"
},
{
"name": "R-gistr",
"description": "Work with GitHub Gists"
},
{
"name": "R-git2r",
"description": "R bindings to the libgit2 library"
},
{
"name": "R-git4r",
"description": "Interactive git for R"
},
{
"name": "R-gitcreds",
"description": "Query git credentials from R"
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{
"name": "R-githubr",
"description": "API wrapper for GitHub"
},
{
"name": "R-GJRM",
"description": "Generalised Joint Regression Modelling"
},
{
"name": "R-gk",
"description": "g-and-k and g-and-h distribution functions"
},
{
"name": "R-glarma",
"description": "Generalized linear autoregressive moving average models"
},
{
"name": "R-glasso",
"description": "Graphical lasso: estimation of gaussian graphical models"
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{
"name": "R-glassoFast",
"description": "Fast graphical lasso"
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{
"name": "R-glba",
"description": "General Linear Ballistic Accumulator models"
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{
"name": "R-glca",
"description": "R Package for multiple-group latent class analysis"
},
{
"name": "R-GLCMTextures",
"description": "GLCM Textures of raster layers"
},
{
"name": "R-gld",
"description": "Estimation and use of the Generalised (Tukey) Lambda distribution"
},
{
"name": "R-GLDEX",
"description": "Fitting single and mixture of generalised Lambda distributions"
},
{
"name": "R-gllvm",
"description": "Generalized Linear Latent Variable Models"
},
{
"name": "R-glm2",
"description": "Fitting Generalized Linear Models"
},
{
"name": "R-glmbb",
"description": "Find all hierarchical models of specified generalized linear model"
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{
"name": "R-glmc",
"description": "Fitting of generalized linear models subject to constraints"
},
{
"name": "R-glmertree",
"description": "Generalized linear mixed model trees"
},
{
"name": "R-glmGamPoi",
"description": "Fit a Gamma-Poisson Generalized Linear Model"
},
{
"name": "R-glmglrt",
"description": "GLRT p-values in generalized linear models"
},
{
"name": "R-glmm",
"description": "Generalized linear mixed models via Monte Carlo likelihood approximation"
},
{
"name": "R-glmm.hp",
"description": "Hierarchical partitioning of marginal R2 for generalized mixed-effect models"
},
{
"name": "R-GLMMadaptive",
"description": "Generalized linear mixed models using adaptive Gaussian quadrature"
},
{
"name": "R-glmmEP",
"description": "Generalized Linear Mixed Model Analysis via Expectation Propagation"
},
{
"name": "R-glmmLasso",
"description": "Variable selection for generalized linear mixed models by l1-penalized estimation"
},
{
"name": "R-glmmML",
"description": "Generalized linear models with clustering"
},
{
"name": "R-glmmPen",
"description": "High-dimensional penalized generalized linear mixed models (pGLMM)"
},
{
"name": "R-glmmrBase",
"description": "Specification of generalised linear mixed models"
},
{
"name": "R-glmmrOptim",
"description": "Approximate optimal experimental designs using generalised linear mixed models"
},
{
"name": "R-GLMMselect",
"description": "Bayesian model selection for generalized linear mixed models"
},
{
"name": "R-glmmTMB",
"description": "Generalized Linear Mixed Models using Template Model Builder"
},
{
"name": "R-glmnet",
"description": "Lasso and elastic-net regularized generalized linear models"
},
{
"name": "R-glmnetUtils",
"description": "Utilities for glmnet"
},
{
"name": "R-GLMpack",
"description": "Data and code to accompany Generalized Linear Models (2nd ed.)"
},
{
"name": "R-GLMsData",
"description": "Data sets from the book Generalized Linear Models with Examples in R"
},
{
"name": "R-glmtoolbox",
"description": "Set of tools to data analysis using generalized linear models"
},
{
"name": "R-glmtrans",
"description": "Transfer learning under regularized generalized linear models"
},
{
"name": "R-glmx",
"description": "Generalized Linear Models Extended"
},
{
"name": "R-GlobalOptions",
"description": "Generate functions to get or set global options"
},
{
"name": "R-globalOptTests",
"description": "Objective functions for benchmarking the performance of global optimization algorithms"
},
{
"name": "R-globals",
"description": "Identify global objects in R expressions"
}
]
}