blinregpred=function(X1,theta.sample)
{
#blinregpred Produces a simulated sample from the posterior predictive
# distribution of a linear regression model
# X1 = design matrix of interest
# theta.sample = output of blinreg function
d=dim(X1)
n1=d[1]
m=length(theta.sample$sigma)
y1=array(0,c(m,n1))
for (j in 1:n1)
{
y1[,j]=t(X1[j,]%*%t(theta.sample$beta))+rnorm(m)*theta.sample$sigma
}
return(y1)
}
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