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### produce summary.rda for Appendix C
load("data.rda")
library("mvtnorm")
library("copula")
set.seed(290875)
method <- factor(c("NP_NP", "mvord"))
i <- which(args$nc == 0)
tmp <- expand.grid(i = i, method = method)
args <- args[tmp$i,]
args$method <- tmp$method
ev <- expression({
tm <- sapply(ret[i], function(x) x$Time %||% NA)
args[args$method == m, "Time"] <- unlist(tm)
rmse <- sapply(i, function(i) {
if (is.null(ret[[i]]$Est)) return(NA)
R <- as.array(invchol2cor(ret[[i]]$Est))[,,1]
RL <- as.array(invchol2cor(attr(d[[i]], "L")))[,,1]
sqrt(sum((R[lower.tri(R)] - RL[lower.tri(RL)])^2))
})
args[args$method == m, "FrobD_R"] <- rmse
})
for (m in levels(method)) {
if (m %in% c("mvord", "copula")) next()
load(paste0("ret_eff_", m, ".rda"))
eval(ev)
}
load("ret_eff_mvord.rda")
tm <- sapply(ret[i], function(x) x$Time %||% NA)
args[args$method == "mvord", "Time"] <- unlist(tm)
rmse <- sapply(i, function(i) {
if (is.null(ret[[i]]$Est)) return(NA)
R <- ret[[i]]$Est
RL <- as.array(invchol2cor(attr(d[[i]], "L")))[,,1]
sqrt(sum((R[lower.tri(R)] - RL[lower.tri(RL)])^2))
})
args[args$method == "mvord", "FrobD_R"] <- rmse
v <- c("N", "J")#, "ncat")
args[,v] <- lapply(v, function(var) {
lev <- sort(unique(args[[var]]))
if (var == "J") lev <- rev(lev)
lab <- paste(var, lev, sep = "=")
factor(args[[var]], levels = lev, labels = lab)
})
args$method <- factor(as.character(args$method), levels = c("mvord", "NP_NP"), labels = c("cML", "NPN"))
save(args, file = "summary.rda")
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