# 1.StatMod

##### Introduction to the StatMod Package

This library packages together those functions, other than those for microarray data analysis, which I wish to make public.

- Keywords
- documentation

##### Generalized Linear Models

`tweedie`

,
`canonic.digamma`

,
`unitdeviance.digamma`

,
`varfun.digamma`

,
`cumulant.digamma`

,
`d2cumulant.digamma`

,
`meanval.digamma`

and `logmdigamma`

are functions to fit non-standard generalized linear models related to the gamma distribution.
`qres`

implements randomized quantile residuals for generalized linear models.

##### Growth Curves

`compareGrowthCurves`

,
`compareTwoGrowthCurves`

and
`meanT`

are functions to test for differences between growth curves with repeated measurements on subjects.

##### Probability Distributions

`qinvgauss`

,
`dinvgauss`

,
`pinvgauss`

and
`rinvgauss`

perform 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.

##### Variance Models

`randomizedBlock`

,
`randomizedBlockFit`

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.

*Documentation reproduced from package statmod, version 1.1.0, License: LGPL version 2 or newer*