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lambda.reg.bayes <- function(object, columns, ret.mcmc = TRUE){
if (inherits(object,"eiRegBayes")==FALSE)
stop("'object' must be output from 'ei.reg.bayes'")
if (missing(columns) | length(columns) < 2)
stop("'columns' requires at least two column names")
lambda.out <- array(NA, dim=c(length(rownames(object$draws)),
length(columns), dim(object$draws)[3]))
rownames(lambda.out) <- rownames(object$draws)
colnames(lambda.out) <- columns
for(i in columns){
lambda.out[,i,] <-
object$draws[,i,]/apply(object$draws[,columns,],c(1,3),sum)
}
if (ret.mcmc){
lambda.out <- t(matrix(lambda.out,
nrow(lambda.out)*ncol(lambda.out),
dim(lambda.out)[3]))
colnames(lambda.out) <- apply(expand.grid(rownames(object$draws),
columns)[,1:2], 1,
paste, collapse=".")
lambda.out <- coda::mcmc(lambda.out)
}
class(lambda.out) <- c("lambdaRegBayes", class(lambda.out))
lambda.out
}
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