post.normal.mean <- function(x, prior.mean, prior.var, data.var)
{
####################################################################
# R function for Bayesian analysis of normal mean, variance known  #
# Parameters included are:                                         #
#                                                                  #
# Inputs:                                                          #
#                                                                  #
# x = vector of data                                               #
# prior.mean = prior mean                                          #
# prior.var = prior variance                                       #
# data.var = assumed known variance of data                        #
#                                                                  #
# Outputs:                                                         #
#                                                                  #
# post.mean = posterior mean                                       #
# post.var = posterior variance                                    #
#                                                                  #
####################################################################
n<- length(x)
x.bar <- mean(x)
post.mean.numerator <- prior.mean/prior.var + n*x.bar/data.var
post.mean.denominator <- 1/prior.var + n/data.var
post.mean <- post.mean.numerator/post.mean.denominator
post.var <- (1/(1/prior.var + n/data.var))
posterior.parameters <- list(post.mean= post.mean, post.var = post.var)
return(posterior.parameters)
}