runsims {mixstock} | R Documentation |
Run multiple simulations of a mixed stock systems with specified marker frequencies and source contributions, running multiple estimations (bootstrap samples or MCMC chains) for each simulation
runsims(sim.n=10, mc.n=10, totsamp=200, which="all", true.freq=matrix(c(0.65, 0.31, 0.01, 0.01, 0.01, 0.01, 0.31,0.65,0.01,0.01,0.01,0.01),ncol=2), true.contrib=c(0.9, 0.1), est="MCMC", verbose=FALSE, fuzz=0.001, nboot=1000, bootrpt=20, minmarks=3)
sim.n |
Number of simulations to run |
mc.n |
Number of bootstrap/MCMC chains to run for each simulation |
totsamp |
total sample size (to be distributed half in mixed stock and half, evenly, among sources) |
which |
which markers to use: "common", "rare", or "all" |
true.freq |
matrix of true marker frequencies in the sources (column=source, row=marker) |
true.contrib |
vector of true contributions of sources to the mixed stock |
est |
estimation method: "MCMC" (Markov Chain Monte Carlo), "cml" (conditional max. likelihood), or "uml" (unconditional max. likelihood) |
verbose |
produce lots of debugging output? |
fuzz |
"fuzz" parameters for (e.g.) keeping estimated values away from 0/1 |
nboot |
Number of bootstrap samples/length of MCMC chain |
bootrpt |
Frequency for reporting on the progress of bootstrap code |
minmarks |
Minimum number of markers to allow for a simulation |
Array of the results from all simulations and bootstrap samples
## mild kluge to drop unneeded dimensions runsims(sim.n=1,mc.n=1,nboot=100,est="cml")[,,]