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

In aliaksah/EMJMCMC2016: EMJMCMC

Obtaining Bayesian estimators of interest from a GLM model

Usage

estimate.bigm(formula, data, family, prior, maxit = 2,chunksize = 1000000)

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	distribution family foe the responces
prior	either "AIC" or "BIC"
maxit	maximum number of Fisher scoring iterations
chunksize	size of chunks for processng the data frame

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
n	sample size

See Also

biglm::bigglm

Examples

library(RCurl)


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)
formula1 = as.formula(paste(colnames(X4)[51],"~ 1 +",paste0(colnames(X4)[-c(51)],collapse = "+")))

formula1 = as.formula(paste(colnames(data.example)[1],"~ 1 +",paste0(colnames(data.example)[-1],collapse = "+")))
estimate.bigm(formula = formula1, data = data.example,n=47,prior = "BIC", maxit = 20,chunksize = 1000000, family = gaussian())

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