MCMC for Generalized Linear Mixed Models with glmmBUGS

被引：0

作者：

Brown, Patrick ^{[1
,2
]}

Zhou, Lutong ^{[2
]}

机构：

[1] Univ Toronto, Dalla Lana Sch Publ Hlth, Toronto, ON M5S 1A1, Canada

[2] Canc Care Ontario, Toronto, ON, Canada

来源：

R JOURNAL | 2010年 / 2卷 / 01期

基金：

加拿大自然科学与工程研究理事会;

关键词：

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

The glmmBUGS package is a bridging tool between Generalized Linear Mixed Models (GLMMs) in R and the BUGS language. It provides a simple way of performing Bayesian inference using Markov Chain Monte Carlo (MCMC) methods, taking a model formula and data frame in R and writing a BUGS model file, data file, and initial values files. Functions are provided to reformat and summarize the BUGS results. A key aim of the package is to provide files and objects that can be modified prior to calling BUGS, giving users a platform for customizing and extending the models to accommodate a wide variety of analyses.

引用

页码：13 / 17

页数：5

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