(This article was first published on

**Shige's Research Blog**, and kindly contributed to R-bloggers)I am doing a simple comparison of different estimation procedures in dealing with a simple binomial model. Here is where I got started:

———————————————

library(INLA)

library(npmlreg)

library(MCMCglmm)

library(DPpackage)

data(Seeds)

# Using INLA

formula = r ~ x1*x2 + f(plate, model=”iid”)

mod.inla = inla(formula, data=Seeds, family=”binomial”, Ntrials=n)

summary(mod.seeds)

# Using npmlreg

mod.ml <- alldist(cbind(r, n-r) ~ x1*x2 , random=~1, data=Seeds, family=binomial, random.distribution=”gq”)

summary(mod.ml)

# Using MCMCglmm

prior <- list(R=list(V=1, nu=0.002))

mod.mcmc <- MCMCglmm(cbind(r, n-r) ~ x1*x2, family=”multinomial2″, data=Seeds, prior=prior)

summary(mod.mcmc$Sol)

# Using DPpackage

———————————————–

I will keep updating by adding new things (estimation procedures, predictive simulations, etc.)

To

**leave a comment**for the author, please follow the link and comment on his blog:**Shige's Research Blog**.R-bloggers.com offers

**daily e-mail updates**about R news and tutorials on topics such as: visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...