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glmmBUGS (version 2.4.2)

Generalised Linear Mixed Models with BUGS and JAGS

Description

Automates running Generalised Linear Mixed Models, including spatial models, with WinBUGS, OpenBUGS and JAGS. Models are specified with formulas, with the package writings model files, arranging unbalanced data in ragged arrays, and creating starting values. The model is re-parameterized, and functions are provided for converting model outputs to the original parameterization.

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Version

Install

install.packages('glmmBUGS')

Monthly Downloads

175

Version

2.4.2

License

GPL

Maintainer

Patrick Brown

Last Published

May 1st, 2018

Functions in glmmBUGS (2.4.2)

getDesignMatrix

Computes a design matrix from factors and interactions
restoreParams

Reparametrise bugs output
rongelapUTM

Rongelap island data
checkChain

Plot an MCMC run
cholInvArray

Precision matrices to variance matrices for Winbugs output
ontarioResult

Ontario Winbugs Results
addSpatial

Calculate adjacency values for WinBUGS
binToBinom

Convert Bernoulli observations to Binomial
popDataAdjMat

Data set containing an adjacency matrix
getStartingValues

Extract starting values for an MCMC chain from glmmPQL results
ontario

Ontario data on molar cancer
muscleResult

data set contains muscle result
startingFunction

Write a function to generate random MCMC starting values
glmmBUGS

A function to run Generalised Linear Mixed Models in Bugs
summaryChain

Compute mean, standard deviation, and quantiles of an MCMC run
glmmPQLstrings

An alternat interface to glmmPQL
mergeBugsData-methods

Merge results from BUGS into a data.frame or SPDF
winBugsRaggedArray

Ragged Arrays for multilevel models in BUGS
writeBugsModel

Write a bugs model file for a Generalised Linear Mixed Model
getRaggedSeq

Get one sequence for a ragged array