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ana_mmlglobal <- function(design, n, r, lambda) {
shape_post <- weight_mmlglobal(design = design, n = n, r = r)
post_prob <- post_beta(shape = shape_post, p0 = design$p0)
ifelse(post_prob >= lambda, 1, 0)
}
weight_mmlglobal <- function(design, n, r) {
shape1_post <- shape2_post <- numeric(design$k)
for (i in 1:design$k) {
f <- function(delta) -extraDistr::dbbinom(
x = r[i],
size = n,
alpha = design$shape1 + sum(delta * r[-i]),
beta = design$shape2 + sum(delta * (n - r[-i]))
)
l <- stats::optim(rep(0.5, design$k - 1), fn = f,
lower = rep(0, design$k - 1), upper = rep(1, design$k - 1),
method = "L-BFGS-B")$par
shape1_post[i] <- design$shape1 + r[i] + sum(l * r[-i])
shape2_post[i] <- design$shape2 + (n - r[i]) + sum(l * (n - r[-i]))
}
matrix(c(shape1_post, shape2_post), nrow = 2, byrow = TRUE)
}
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