estimate.bigm: Obtaining Bayesian estimators of interest from a GLM model In aliaksah/EMJMCMC2016: EMJMCMC

Usage

 `1` ```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

 ``` 1 2 3 4 5 6 7 8 9 10 11 12``` ```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()) ```