estimate.bas.glm: Obtaining Bayesian estimators of interest from a GLM model

In aliaksah/EMJMCMC2016: EMJMCMC

Obtaining Bayesian estimators of interest from a GLM model

Usage

estimate.bas.glm(formula, data, family, prior, logn)

Arguments

formula	a formula object for the model to be addressed
data	a data frame object containing variables and observations corresponding to the formula used
family	either poisson() or binomial(), that are currently adopted within this function
prior	aic.prior(),bic.prior() or ic.prior() are allowed
logn	log sample size

Value

A list of

mlik	marginal likelihood of the model
waic	AIC model selection criterion
dic	BIC model selection criterion
summary.fixed$mean	a vector of posterior modes of the parameters

See Also

BAS::bayesglm.fit

Examples

X4= as.data.frame(array(data = rbinom(n = 50*1000,size = 1,prob = runif(n = 50*1000,0,1)),dim = c(1000,50)))
Y4=rnorm(n = 1000,mean = 1+7*(X4$V4*X4$V17*X4$V30*X4$V10)+7*(((X4$V50*X4$V19*X4$V13*X4$V11)>0)) + 9*(X4$V37*X4$V20*X4$V12)+ 7*(X4$V1*X4$V27*X4$V3)
             +3.5*(X4$V9*X4$V2) + 6.6*(X4$V21*X4$V18) + 1.5*X4$V7 + 1.5*X4$V8,sd = 1)
X4$Y4=Y4
data.example = as.data.frame(X4)
data.example$Y4=as.integer(data.example$Y>mean(data.example$Y))
formula1 = as.formula(paste(colnames(X4)[51],"~ 1 +",paste0(colnames(X4)[-c(51)],collapse = "+")))

estimate.bas.glm(formula = formula1, data = data.example,prior = aic.prior(), logn=47, family = binomial())

aliaksah/EMJMCMC2016 documentation built on July 27, 2023, 5:48 a.m.