# R/multivspost2blog.R In CARrampsOcl: Reparameterized and marginalized posterior sampling for conditional autoregressive models, OpenCL implementation

#### Documented in multivspost2blog

```multivspost2blog <-
function(smat, alpha, beta, D, y, By, k )
{
# computes posterior marginal of S in He/Hodges model
# called by optimization function
# alpha = c(alphae, alphaz_1 to alphaz_{F-1})
# beta = c(betae, betaz_1 to betaz_{F-1})

# D:  matrix of diagonals of the diagonal matrices from diag of Q matrices
# k is rank deficiency of sum(Q's); i.e., rank of Q is n-k
# smat is matrix with F-1 cols; each row is s_1 to s_{F-1}

smat <- as.matrix(smat)
n <- length(y)

F <- ncol(D) + 1

sums <- apply(D,1,sum)
#k <- length( sums[sums==0] )

logpostvect <- numeric()
tausqtot <- numeric()

sumalpha <- sum(alpha)

s <- smat
s0 <- 1-sum(s)

neweigennumer <- s * D[,1]
if (F > 2)
for(j in 2:(F-1))
neweigennumer <- neweigennumer + s[j] * D[,j]
neweigendenom <-  neweigennumer + s0

neweigen <- s0 * neweigennumer / neweigendenom
# corrected to (alpha-1) 09/18/09
#logpostdensnumer <- sum( log(c(s0,s)) * alpha ) +
logpostdensnumer <- sum( log(c(s0,s)) * (alpha-1) ) +
sum( log(neweigen[ neweigen > 0 ]) ) / 2
#       whole <- sum( neweigen * Bysq )
whole <- sum( neweigen * By^2 )

newbeta <- whole/2 +  sum( c(s0,s) * beta )
newalpha <- (sumalpha + (n-k)/2 )
logpostdensdenom <-  log( newbeta)* newalpha
logpostvect <- logpostdensnumer - logpostdensdenom

logpostvect

}
```

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CARrampsOcl documentation built on May 2, 2019, 3:27 a.m.