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### Log likelihood function for puniform with ML method
ml <- function(d, yi, vi, zcv)
{
q <- mapply(function(d, yi, vi, zcv)
{
### In case of extreme conditional density, use approximation
ifelse(yi/sqrt(vi)-d/sqrt(vi) < 36,
dnorm(yi/sqrt(vi), mean = d/sqrt(vi), sd = 1)/
exp(pnorm(zcv, mean = d/sqrt(vi), sd = 1, lower.tail = FALSE, log.p = TRUE)),
approx_puni(zd = d/sqrt(vi), zval = yi/sqrt(vi), zcv = zcv, method = "ML"))
}, yi = yi, zcv = zcv, vi = vi, MoreArgs = list(d = d))
log(prod(q))
}
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