r4ss (version 1.24.0)

SS_profile: Run a likelihood profile in Stock Synthesis.

Description

Iteratively changes the control file using SS_changepars.

Usage

SS_profile(dir = "C:/myfiles/mymodels/myrun/",
  masterctlfile = "control.ss_new", newctlfile = "control_modified.ss",
  linenum = NULL, string = NULL, profilevec = NULL, usepar = FALSE,
  globalpar = FALSE, parfile = NULL, parlinenum = NULL,
  parstring = NULL, dircopy = TRUE, exe.delete = FALSE, model = "ss3",
  extras = "-nox", systemcmd = FALSE, saveoutput = TRUE,
  overwrite = TRUE, whichruns = NULL, verbose = TRUE)

Arguments

dir

Directory where input files and executable are located.

masterctlfile

Source control file. Default = "control.ss_new"

newctlfile

Destination for new control files (must match entry in starter file). Default = "control_modified.ss".

linenum

Line number of parameter to be changed. Can be used instead of string or left as NULL.

string

String partially matching name of parameter to be changed. Can be used instead of linenum or left as NULL.

profilevec

Vector of values to profile over. Default = NULL.

usepar

Use PAR file from previous profile step for starting values?

globalpar

Use global par file for all runs instead of the par file from each successive run

parfile

Name of par file to use (Ian says "I don't remember how this interacts with the globalpar input")

parlinenum

Line number in par file to change.

parstring

String in par file preceding line number to change.

dircopy

Copy directories for each run? NOT IMPLEMENTED YET.

exe.delete

Delete exe files in each directory? NOT IMPLEMENTED YET.

model

Name of executable. Default = "ss3".

extras

Additional commands to use when running SS. Default = "-nox" will reduce the amound of command-line output.

systemcmd

Should R call SS using "system" function intead of "shell". This may be required when running R in Emacs. Default = FALSE.

saveoutput

Copy output .SSO files to unique names. Default = TRUE.

overwrite

Overwrite any existing .SSO files. Default = TRUE. If FALSE, then some runs may be skipped.

whichruns

Optional vector of run indices to do. This can be used to re-run a subset of the cases in situations where the function was interupted or some runs fail to converge. Must be a subset of 1:n, where n is the length of profilevec.

verbose

Controls amount of info output to command line. Default = TRUE.

See Also

SSplotProfile, SSgetoutput, SS_changepars, SS_parlines

Examples

# NOT RUN {
  
# }
# NOT RUN {
# note: don't run this in your main directory
# make a copy in case something goes wrong
mydir <- "C:/ss/Simple - Copy"

# the following commands related to starter.ss could be done by hand
# read starter file
starter <- SS_readstarter(file.path(mydir, 'starter.ss'))
# change control file name in the starter file
starter$ctlfile <- "control_modified.ss"
# make sure the prior likelihood is calculated
# for non-estimated quantities
starter$prior_like <- 1
# write modified starter file
SS_writestarter(starter, dir=mydir, overwrite=TRUE)

# vector of values to profile over
h.vec <- seq(0.3,0.9,.1)
Nprofile <- length(h.vec)

# run SS_profile command
profile <- SS_profile(dir=mydir, # directory
                      # "NatM" is a subset of one of the
                      # parameter labels in control.ss_new
                      model="ss3_safe",
                      masterctlfile="control.ss_new",
                      newctlfile="control_modified.ss",
                      string="steep",
                      profilevec=h.vec)


# read the output files (with names like Report1.sso, Report2.sso, etc.)
profilemodels <- SSgetoutput(dirvec=mydir, keyvec=1:Nprofile)
# summarize output
profilesummary <- SSsummarize(profilemodels)

# OPTIONAL COMMANDS TO ADD MODEL WITH PROFILE PARAMETER ESTIMATED
MLEmodel <- SS_output("C:/ss/SSv3.24l_Dec5/Simple")
profilemodels$MLE <- MLEmodel
profilesummary <- SSsummarize(profilemodels)
# END OPTIONAL COMMANDS

# plot profile using summary created above
SSplotProfile(profilesummary,           # summary object
              profile.string = "steep", # substring of profile parameter
              profile.label="Stock-recruit steepness (h)") # axis label

# make timeseries plots comparing models in profile
SSplotComparisons(profilesummary,legendlabels=paste("h =",h.vec))

# }
# NOT RUN {
# }