rm(list = ls())
library("rstream")
# dimension of observations for Sasaki data
D <- 77
# load the last saved rngstream offset object
prev_setting <- "lab"
prev_location <- "wrist"
prev_fit_method <- "RFHMM"
prev_case <- "2stage_stage2"
prev_subj <- 35L
prev_stream_filename <- paste("rngstream_Sasaki", prev_setting, prev_location, prev_fit_method, "case", prev_case, "subj", prev_subj, sep = "_")
load(file = paste0("C:/Stat/HMM/HMMEnsembles/rayThesis/inst/appliedPAClassificationScripts/Sasaki/intensity/rngstreams/", prev_stream_filename, ".rdata"))
rstream.packed(rngstream) <- FALSE
# advance the corresponding number of substreams: 25302
for(i in seq_len(25302)) {
rstream.nextsubstream(rngstream)
}
# possible levels for method
new_fit_method <- "unpenalizedParametricCRF"
# number of substreams used per subject: 1
num_substreams_used <- 1
for(setting in c("freeliving", "lab")) {
# number of subjects
if(identical(setting, "freeliving")) {
N <- 15
} else {
N <- 35
}
for(location in c("ankle", "hip", "wrist")) {
# create rstream object with a new seed. For programming simplicity and reduced computation time,
# we use a new seed for each combination of setting, location, and class_var,
# with the same seed value (but different substreams used) for levels of
# fit_method, reduced_trans_mat_parameterization, and update_trans within
# the combination of setting, location, and class_var.
# The seed values are randomly generated.
# Get rng substream offset corresponding to the combination of fit_method, reduced_trans_mat_parameterization, and update_trans:
for(case in c("1stage", "1stageusingtrueclass")) {
for(subj in seq_len(N)) {
rstream.packed(rngstream) <- TRUE
stream_filename <- paste("rngstream_Sasaki", setting, location, new_fit_method,
"case", case, "subj", subj, sep = "_")
save(rngstream, file = paste0("C:/Stat/HMM/HMMEnsembles/rayThesis/inst/appliedPAClassificationScripts/Sasaki/intensity/rngstreams/", stream_filename, ".rdata"))
save(rngstream, file = paste0("C:/Program Files/R/R-3.0.2/library/rayThesis/appliedPAClassificationScripts/Sasaki/intensity/rngstreams/", stream_filename, ".rdata"))
rstream.packed(rngstream) <- FALSE
for(i in seq_len(num_substreams_used)) {
rstream.nextsubstream(rngstream)
}
} # subj
} # truth
} # location
} # setting
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