R: Introduction to the StatMod Package

statmod-package {statmod} | R Documentation

## Introduction to the StatMod Package

### Description

This package includes a variety of functions for numerical analysis and statistical modelling. The functions are briefly summarized by type of application below.

### Generalized Linear Models

The function `tweedie` defines a large class of generalized linear model families with power variance functions. It used in conjunction with the glm function, and widens the class of families that can be fitted.

`qresiduals` implements randomized quantile residuals for generalized linear models.

The functions `canonic.digamma`, `unitdeviance.digamma`, `varfun.digamma`, `cumulant.digamma`, `d2cumulant.digamma`, `meanval.digamma` and `logmdigamma` are used to fit double-generalized models, in which a link-linear model is fitted to the dispersion as well as to the mean. Spefically they are used to fit the dispersion submodel associated with a gamma glm.

### Growth Curves

`compareGrowthCurves`, `compareTwoGrowthCurves` and `meanT` are functions to test for differences between growth curves with repeated measurements on subjects.

### Limiting Dilution Analysis

The `limdil` function is used in the analysis of stem cell frequencies. It implements limiting dilution analysis using complemenary log-log binomial generalized linear model regression, with some improvements on previous programs.

### Probability Distributions

The functions `qinvgauss`, `dinvgauss`, `pinvgauss` and `rinvgauss` provide probability calculations for the inverse Gaussian distribution.

`gauss.quad` and `gauss.quad.prob` compute Gaussian Quadrature with probability distributions.

### Tests

`hommel.test` performs Hommel's multiple comparison tests.

`power.fisher.test` computes the power of Fisher's Exact Test for comparing proportions.

`sage.test` is a fast approximation to Fisher's exact test for each tag for comparing two Serial Analysis of Gene Expression (SAGE) libraries.

`permp` computes p-values for permutation tests when the permutations are randomly drawn.

### Variance Models

`mixedModel2`, `mixedModel2Fit` and `glmgam.fit` fit mixed linear models.

`remlscore` and `remlscoregamma` fit heteroscedastic and varying dispersion models by REML. `welding` is an example data set.

### Matrix Computations

`matvec` and `vecmat` facilitate multiplying matrices by vectors.

### Author(s)

Gordon Smyth

[Package statmod version 1.4.36 Index]