Nothing
res <- expand.grid(i = 1:NSIM, m = 1:length(model))
simfun <- function(m, i) {
cat("m: ", m, " i: ", i, "\n")
ret <- c("boost_ll" = NA, "true_ll" = NA, "mlt_ll" = NA, "mstop" = NA)
if (PNON > 0) {
### mean centered
Xnon <- matrix(runif(nrow(d) * PNON), ncol = PNON) - .5
colnames(Xnon) <- paste("nx", 1:PNON, sep = "")
d <- cbind(d, Xnon)
}
idx <- sample(1:nrow(d), 2 * NOBS, replace = FALSE)
ind <- d[idx,,drop = FALSE]
ind$y <- y[[m]][[i]][idx]
test <- d
test$y <- y[[m]][[NSIM + i]]
t0 <- mlt(model[[m]], data = test, theta = coef(model[[m]]),
dofit = FALSE)
coef(t0) <- coef(model[[m]])
print(ret["true_ll"] <- logLik(t0))
t1 <- mlt(model[[m]], data = ind, theta = coef(model[[m]]))
print(ret["mlt_ll"] <- logLik(t1, newdata = test))
w <- rep(c(1, 0), each = NOBS)
### mean centering for boosting
ind$x2 <- ind$x2 - .5
test$x2 <- test$x2 - .5
l1 <- try(FUN(ind, w))
if (!inherits(l1, "try-error")) {
print(ret["boost_ll"] <- logLik(l1$model, newdata = test,
parm = coef(l1, newdata = test)))
ret["mstop"] <- mstop(l1)
}
cat("----\n")
return(ret)
}
mc.reset.stream()
x <- mclapply(1:NROW(res),
function(r) simfun(res[r, "m"], res[r, "i"]), mc.cores = MC_CORES)
res <- cbind(res, do.call("rbind", x))
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