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SSbootstrap <- function(){
# this is not yet a generalized function, just some example code for how to do
# a parametric bootstrap such as was done for the Pacific hake model in 2006
# See http://www.pcouncil.org/wp-content/uploads/2006_hake_assessment_FINAL_ENTIRE.pdf
# A description is on page 41 and Figures 55-56 (pg 139-140) show some results.
# Written by Ian Taylor on 10/11/2012 after disucussion with Nancie Cummings
# first set "Number of datafiles to produce" in starter.ss = 100 or some large number
# re-run model to get data.ss_new file concatenating all bootstrap data files
# Directory where bootstrap will be run.
# You probably want to use a copy of the directory where you ran it,
# so as not to overwrite the true results.
inpath <- 'c:/Simple'
#setwd(inpath) # change working directory (commented out to avoid violating CRAN policy)
# split apart data.ss_new into multiple data files with names like "BootData1.ss"
SS_splitdat(inpath=inpath, outpath=inpath, number=TRUE, MLE=FALSE)
N <- 10 # number of bootstrap models to run (less than or equal to setting in starter)
starter <- SS_readstarter(file="starter.ss") # read starter file
file.copy("starter.ss","starter_backup.ss") # make backup
# loop over bootstrap files
for(iboot in 1:N){
# note what's happening
cat("\n##### Running bootstrap model number",iboot," #########\n")
# change data file name in starter file
starter$datfile <- paste("BootData",iboot,".ss",sep="")
# replace starter file with modified version
SS_writestarter(starter, overwrite=TRUE)
# delete any old output files
file.remove("Report.sso")
file.remove("CompReport.sso")
file.remove("covar.sso")
# run model
shell("SS3")
# for some computers or versions of R, "shell" works better than "system"
#system("ss3")
# copy output files (might be good to use "file.exists" command first to check if they exist
file.copy("Report.sso",paste("Report_",iboot,".sso",sep=""))
file.copy("CompReport.sso",paste("CompReport_",iboot,".sso",sep=""))
file.copy("covar.sso",paste("covar_",iboot,".sso",sep=""))
# other .sso files could be copied as well
}
# read and summarize all models
# (setting getcomp=FALSE will produce warning
# about missing comp file, but use less memory)
bootmodels <- SSgetoutput(keyvec=paste("_",1:N,sep=""), dirvec=inpath, getcomp=FALSE)
bootsummary <- SSsummarize(bootmodels)
# a bunch of plots that won't work well if there are lots of models
SSplotComparisons(bootsummary,png=TRUE)
# histogram of a single quantity
hist(as.numeric(bootsummary$quants[bootsummary$quants$Label=="SPB_Virgin",1:N]))
hist(as.numeric(bootsummary$pars[grep("R0",bootsummary$pars$Label),1:N]))
}
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