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
收藏
页码：13 / 17
页数：5
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