Nothing
post_RA_fits <- function(fits.actual, fits.bm,
H.dist.method = "integral"){
# inputs:
# fits.actual: a list of bayesmeta fits under actual priors
# fits.bm: a list of bayesmeta fits under benchmark priors,
# with "most extreme" benchmarks first and last
# output:
# matrix with (k+3) rows and length(fits.bm)+1 columns giving
# the Hellinger distances betw. marginal posteriors for different parameters
# under the actual prior vs. one benchmark prior,
# and the Hellinger distance betw. the 2 most extreme benchmarks
k <- fits.actual[[1]]$k
n.bm <- length(fits.bm)
n.act <- length(fits.actual)
n.row <- (3+k)*n.act
# p <- length(fits.bm)+1
tab.H <- matrix(nrow=n.row, ncol=n.bm)
# loop over parameters
# for(m in 1:(k+3)){
# ii <- (m-1)*n.act
for(i in 1:n.act){
# fit.actual <- fits.actual[[i]]
# ii <- (i -1)*(k+3)
for(j in 1:n.bm){
ii <- 0
tab.H[ii+i,j] <- H_fits(fits.actual[[i]], fits.bm[[j]],
parameter = "mu", method = H.dist.method)
ii <- 1*n.act
tab.H[ii+i,j] <- H_fits(fits.actual[[i]], fits.bm[[j]],
parameter = "tau", method = H.dist.method)
for(l in 2:(k+1)){
ii <- l*n.act
tab.H[ii+i,j] <- H_fits(fits.actual[[i]], fits.bm[[j]],
parameter = "theta", individual=l-1,
method = H.dist.method)
}
ii <- (k+2)*n.act
tab.H[ii+i,j] <- H_fits(fits.actual[[i]], fits.bm[[j]],
parameter = "theta_new", method = H.dist.method)
}
}
colnames <- rep(NA, times = n.bm)
for(j in 1:n.bm){
colnames[j] <- paste0("H(po_{bm_",j,"}, po_act)", sep="")
}
rownames.mu <- rep(NA, times = n.act)
rownames.tau <- rep(NA, times = n.act)
rownames.theta.new <- rep(NA, times = n.act)
rownames.theta.i <- rep(NA, times = n.act*k)
for(j in 1:n.act){
rownames.mu[j] <- paste0("mu, pri_act_",j, sep="")
rownames.tau[j] <- paste0("tau, pri_act_",j, sep="")
rownames.theta.new[j] <- paste0("theta_new, pri_act_",j, sep="")
for(i in 1:k){
ii <- (i-1)*n.act
rownames.theta.i[ii+j] <- paste0("theta_",i, ", pri_act_",j, sep="")
}
}
rownames <- c(rownames.mu, rownames.tau,
rownames.theta.i, rownames.theta.new)
colnames(tab.H) <- colnames
rownames(tab.H) <- rownames
return(tab.H)
}
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