Nothing
# simple nonparametric bootstrap implementation.
bootstrap.backend = function(data, statistic, R, m, algorithm,
algorithm.args = list(), statistic.args = list(), cluster = NULL,
debug = FALSE) {
# allocate the result list.
res = as.list(seq(R))
bootstrap.replicate = function(r, data, m, algorithm, algorithm.args,
statistic, statistic.args, debug) {
if (debug) {
cat("----------------------------------------------------------------\n")
cat("* bootstrap replicate", r, ".\n")
}#THEN
# generate the r-th bootstrap sample by resampling with replacement.
resampling = sample(nrow(data), m, replace = TRUE)
# user-provided lists of manipulated observations for the mbde score must
# be remapped to match the bootstrap sample.
if (!is.null(algorithm.args$score) && (algorithm.args$score == "mbde") &&
!is.null(algorithm.args$exp)) {
algorithm.args$exp = lapply(algorithm.args$exp, function(x) {
x = match(x, resampling)
x = x[!is.na(x)]
})
}#THEN
# generate the bootstrap sample.
replicate = data[resampling, , drop = FALSE]
if (debug)
cat("* learning bayesian network structure.\n")
# learn the network structure from the bootstrap sample.
bn = do.call(algorithm, c(list(x = replicate), algorithm.args))
if (debug) {
print(bn)
cat("* computing user-defined statistic.\n")
}#THEN
# apply the user-defined function to the newly-learned bayesian network;
# the bayesian network is passed as the first argument hoping it will end
# at the right place thanks to the positional matching.
res = do.call(statistic, c(list(bn), statistic.args))
if (debug) {
cat(" > the function returned:\n")
print(res)
}#THEN
return(res)
}#BOOTSTRAP.REPLICATE
if (!is.null(cluster)) {
res = parallel::parLapplyLB(cluster, res, bootstrap.replicate, data = data,
m = m, algorithm = algorithm,
algorithm.args = algorithm.args, statistic = statistic,
statistic.args = statistic.args, debug = debug)
}#THEN
else {
res = lapply(res, bootstrap.replicate, data = data, m = m,
algorithm = algorithm, algorithm.args = algorithm.args,
statistic = statistic, statistic.args = statistic.args,
debug = debug)
}#ELSE
return(res)
}#BOOTSTRAP.BACKEND
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