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Summarize nuisance MCMC output (used in combination with mcmc.out() for key parameters).

Usage

mcmc.nuisance(
  directory = "c:/mydirectory/",
  run = "mymodel/",
  file = "posteriors.sso",
  file2 = "derived_posteriors.sso",
  bothfiles = FALSE,
  printstats = FALSE,
  burn = 0,
  header = TRUE,
  thin = 1,
  trace = 0,
  labelstrings = "all",
  columnnumbers = "all",
  sep = ""
)

Arguments

directory

Directory where all results are located, one level above directory for particular run.

run

Directory with files from a particular run.

file

Filename either with full path or relative to working directory.

Contents of the file that is referenced here should contain posterior samples for nuisance parameters, e.g., posteriors.sso or something written by SSgetMCMC.

file2

Optional second file containing posterior samples for nuisance parameters. This could be derived_posteriors.sso.

bothfiles

TRUE/FALSE indicator on whether to read file2 in addition to file1.

printstats

Return all the statistics for a closer look.

burn

Optional burn-in value to apply on top of the option in the starter file and SSgetMCMC().

header

Data file with header?

thin

Optional thinning value to apply on top of the option in the starter file, in the mcsave runtime command, and in SSgetMCMC().

trace

Plot trace for param # (to help sort out problem parameters).

labelstrings

Vector of strings that partially match the labels of the parameters you want to consider.

columnnumbers

Vector of column numbers indicating the columns you want to consider.

sep

Separator for data file passed to the read.table function.

Author

Ian Stewart