Package: statmod 1.5.1

statmod: Statistical Modeling

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

Authors:Gordon Smyth [cre, aut], Lizhong Chen [aut], Yifang Hu [ctb], Peter Dunn [ctb], Belinda Phipson [ctb], Yunshun Chen [ctb]

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statmod.pdf |statmod.html✨
statmod/json (API)
NEWS

# Install 'statmod' in R:
install.packages('statmod', repos = c('https://gksmyth.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • welding - Data: Tensile Strength of Welds

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

fortran

9.89 score 1 stars 891 packages 2.6k scripts 115k downloads 55 mentions 50 exports 0 dependencies

Last updated from:f4ad49172e. Checks:13 OK. Indexed: yes.

TargetResultTotal timeArtifact
linux-devel-arm64OK108
linux-devel-x86_64OK116
source / vignettesOK134
linux-release-arm64OK97
linux-release-x86_64OK103
macos-devel-arm64OK82
macos-devel-x86_64OK146
macos-release-arm64OK85
macos-release-x86_64OK162
windows-develOK153
windows-releaseOK135
windows-oldrelOK123
wasm-releaseOK105

Exports:canonic.digammacompareGrowthCurvescompareTwoGrowthCurvescumulant.digammad2cumulant.digammaDigammadinvgausseldaeldaOneGroupexpectedDeviancefitNBPforwardgauss.quadgauss.quad.probglm.scoretestglmgam.fitglmnb.fithommel.testlimdillogmdigammamatvecmeanTmeanval.digammamixedModel2mixedModel2FitmscalepermppinvgaussplotGrowthCurvespower.fisher.testqinvgaussqres.binomqres.defaultqres.gammaqres.invgaussqres.nbinomqres.poisqres.tweedieqresidqresidualsrandomizedBlockrandomizedBlockFitremlscoreremlscoregammarinvgausssage.testtweedieunitdeviance.digammavarfun.digammavecmat

Dependencies:

Readme and manuals

Help Manual

Help pageTopics
Introduction to the StatMod Packagestatmod-package statmod
Digamma Generalized Linear Model Familycanonic.digamma cumulant.digamma d2cumulant.digamma Digamma meanval.digamma unitdeviance.digamma varfun.digamma
Extreme Limiting Dilution Analysiselda eldaOneGroup limdil limdil-class limdil.class
Expected Value of Scaled Unit Deviance for Linear Exponential FamiliesexpectedDeviance
Negative Binomial Model for SAGE Libraries with Pearson Estimation of DispersionfitNBP
Forward Selection of Covariates for Multiple Regressionforward
Gaussian Quadraturegauss.quad
Gaussian Quadrature with Probability Distributionsgauss.quad.prob
Score Test for Adding a Covariate to a GLMglm.scoretest
Fit Gamma Generalized Linear Model by Fisher Scoring with Identity Linkglmgam.fit
Fit Negative Binomial Generalized Linear Model with Log-Linkglmnb.fit
Compare Groups of Growth CurvescompareGrowthCurves compareTwoGrowthCurves plotGrowthCurves
Test Multiple Comparisons Using Hommel's Methodhommel.test
Inverse Gaussian Distributiondinvgauss InverseGaussian pinvgauss qinvgauss rinvgauss
Log Minus Digamma Functionlogmdigamma
Multiply a Matrix by a Vectormatvec vecmat
Mean t-Statistic Between Two Groups of Growth CurvesmeanT
Fit Mixed Linear Model with 2 Error ComponentsmixedModel2 mixedModel2Fit randomizedBlock randomizedBlockFit
M Scale Estimationmscale
Exact permutation p-valuespermp
Plot or print an object of class limdilplot.limdil print.limdil
Power of Fisher's Exact Test for Comparing Proportionspower.fisher.test
Randomized Quantile Residualsqres.binom qres.default qres.gamma qres.invgauss qres.nbinom qres.pois qres.tweedie qresid qresiduals
REML for Heteroscedastic Regressionremlscore
Approximate REML for Gamma Regression with Structured Dispersionremlscoregamma
Exact Binomial Tests For Comparing Two SAGE Libraries (Obsolete)sage.test
Tweedie Generalized Linear Modelstweedie
Data: Tensile Strength of Weldswelding
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