#' Compute the marginal likelihood for Bayesian Strauss inference
#'
marginal_likelihood <- function(stats, R, bbox, priors, mciter=1000){
stop("Not yet implemented.")
samp <- function(n) {
cbind(beta=rgamma(n, priors$beta[1], priors$beta[2]),
gamma=rbeta(n, priors$gamma[1], priors$gamma[2]))
}
pf <- function(bg) (stats[1]*log(bg[1])+stats[2]*log(bg[2])-approximate_strauss_constant(bg[1],bg[2], R, bbox))
grid <- samp(1000)
p <- apply(grid, 1, pf)
mean(p, na.rm=T)
}
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