Posterior.phi <- function(counts, sf, D, R,
phi.mom = NULL,
theta.mom = NULL){
### this function is used to get posterior estimate of phi
x = counts[, seq(1, ncol(counts), 2)] # input
y = counts[, seq(2, ncol(counts), 2)] # ip
if(is.null(sf)){
sf = colSums(counts, na.rm = TRUE)/median(
colSums(counts, na.rm = TRUE))
}
sf.x = sf[seq(1, ncol(counts), 2)]
sf.y = sf[seq(2, ncol(counts), 2)]
### get the posterior of phi
phi.bar = mean(phi.mom, na.rm = TRUE)
s2phi = var(phi.mom, na.rm = TRUE)
mlphi = log(phi.bar + 0.00001) - (1/2)*log(s2phi/(phi.bar)^2 + 1)
sdlphi = sqrt(log(s2phi/(phi.bar)^2 + 1))
### get posterior of phi
res = PostPhi.NBlogN(y = y, x = x, sy = sf.y, sx = sf.x,
D = D, R = R, theta = theta.mom,
mlphi = mlphi, sdlphi = sdlphi)
return(res)
}
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