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I am doing a simple comparison of different estimation procedures in dealing with a simple binomial model. Here is where I got started:Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
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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
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I will keep updating by adding new things (estimation procedures, predictive simulations, etc.)
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