Description Details Author(s) References Examples
The package provides functions which perform Bayesian estimation via Metropolis-Hastings algorithm in generalized linear models.
Package: | bglm |
Type: | Package |
Version: | 1.0 |
Date: | 2014-10-29 |
License: | GPL-2 |
Depends: | mvtnorm |
Nicolas Molano-Gonzalez, Edilberto Cepeda-Cuervo
Maintainer: Nicolas Molano-Gonzalez <nmolanog@unal.edu.co>
Gamerman, D. 1997. Sampling from the posterior distribution in generalized linear mixed models. Statistics and Computing, 7, 57-68.
1 2 3 4 5 6 7 8 9 | library(faraway)
data(babyfood)
summary(babyfood)
g2<- glm(cbind(disease, nondisease) ~ sex+food,family=binomial,babyfood)
#####use N > 8000 for more accurate results
bmen<-binommh(disease~ sex+food,babyfood$disease+babyfood$nondisease,N=1000,
data=babyfood)
data.frame(R.coef=coef(g2),R.sd=sqrt(diag(summary(g2)$cov.unscaled)),
mh.mean=apply(bmen$chain,2,mean),mh.sd=apply(bmen$chain,2,sd))
|
Loading required package: mvtnorm
disease nondisease sex food
Min. :16.00 Min. :111.0 Boy :3 Bottle:2
1st Qu.:22.00 1st Qu.:180.0 Girl:3 Breast:2
Median :39.00 Median :358.5 Suppl :2
Mean :39.67 Mean :306.0
3rd Qu.:47.75 3rd Qu.:420.0
Max. :77.00 Max. :447.0
R.coef R.sd mh.mean mh.sd
(Intercept) -1.6127038 0.1124100 -1.6304421 0.05709493
sexGirl -0.3125528 0.1410397 -0.3026019 0.06999519
foodBreast -0.6692946 0.1530057 -0.6710544 0.07394914
foodSuppl -0.1725424 0.2055847 -0.1953992 0.11263090
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