biv.norm.post {BaM} R Documentation

## biv.norm.post

### Description

A function to calculate posterior quantities of the bivariate normal. See page 94.

### Usage

biv.norm.post(data.mat,alpha,beta,m,n0=5)


### Arguments

 data.mat A matrix with two columns of normally distributed data alpha Wishart first (scalar) parameter beta Wishart second (matrix) parameter m prior mean for mu n0 prior confidence parameter

### Value

Returns

 mu2 posterior mean, dimension 1 sig1 posterior mean, dimension 2 sig2 posterior variance, dimension 1 rho posterior variance, dimension 2

Jeff Gill

### Examples


rwishart <- function(df, p = nrow(SqrtSigma), SqrtSigma = diag(p))  {
if((Ident <- missing(SqrtSigma)) && missing(p)) stop("either p or SqrtSigma must be specified")
Z <- matrix(0, p, p)
diag(Z) <- sqrt(rchisq(p, df:(df-p+1)))
if(p > 1) {
pseq <- 1:(p-1)
Z[rep(p*pseq, pseq) + unlist(lapply(pseq, seq))] <- rnorm(p*(p-1)/2)
}
if(Ident) crossprod(Z)
else crossprod(Z %*% SqrtSigma)
}

data.n10 <- rmultinorm(10, c(1,3), matrix(c(1.0,0.7,0.7,3.0),2,2))
rep.mat <- NULL; reps <- 1000
for (i in 1:reps){
rep.mat <- rbind(rep.mat, biv.norm.post(data.n10,3, matrix(c(10,5,5,10),2,2),c(2,2)))
}
round(normal.posterior.summary(rep.mat),3)



[Package BaM version 1.0.3 Index]