Nothing

```
bprobit.probs=function(X1,fit)
{
# bprobit.probs Produces a simulated sample from the posterior
# distribution of an expected response for a linear regression model
# X1 = design matrix of interest
# fit = output of bayes.probit function
d=dim(X1)
n1=d[1]
md=dim(fit); m=md[1]
m1=array(0,c(m,n1))
for (j in 1:n1)
{
m1[,j]=pnorm(X1[j,]%*%t(fit))
}
return(m1)
}
```

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