makeAssessment: Makes assessment of a fish stock given weight frequency data...

In alko989/s6model: Data-poor stock assessment using a single-sepcies steady-state size-based (s6) model

Makes assessment of a fish stock given weight frequency data for several years

Description

Makes assessment of a fish stock given weight frequency data for several years

Usage

makeAssessment(inputData, yield = NULL, a.mean = 0.22, a.sd = 0.7,
  nsample = 100, same.as = TRUE, u = 10, sigma = NULL, binsize = NULL,
  winf.ubound = 2, equalWinf = TRUE, probs = seq(0, 1, 0.01),
  seed = as.integer(rnorm(1, 1000, 100)), dirout = "results",
  fnout = format(Sys.time(), "results_%Y%m%d_%H%M.RData"), ...)

Arguments

inputData	list of data.frames, each data.frame has columns Weight and Freq and attribute binsize
yield	numeric, the total yearly catch or landings in kg. Use NULL if not known.
a.mean	numeric, physiological mortality.
a.sd	numeric, the standard deviation (log domain) of the log-normal distribution of physiological mortality.
nsample	integer, number of repetitions for uncertainty etimation. If zero no uncertainty is estimated.
same.as	logical, if TRUE use the same random values of physiological mortality for each year.
u	numeric, the selectivity steepness parameter.
sigma	numeric, if NULL the parameter is estimated, otherwise a constant is used, see Details.
binsize	numeric, span of weight classes in grams.
winf.ubound	numeric, the upper bound of asymptotic weight. It is a multiplier of the maximum observed weight.
equalWinf	logical, if TRUE estimate one asymptotic weight for all years, if FALSE estimate one for each year.
probs	numeric vector of probabilites with values in [0,1] for the uncertainty sample quantiles.
seed	numeric, the random number generator seed.
dirout	Output directory
fnout	Output file name
...	Arguments passed to estimate_TMB that does the estimation

Details

• sigma paramter for more information see the cited paper.

Value

object of class s6modelResults which is a data.frame with parameter estimates with attributes

CI

confidence levels as sample quantiles

obj

the TMB object of the default value estimation

opt

the optimization output from nlminb

opts

the input options used in the run

Results

all results using default parameters

seed

the random number gernerator used

timeToCompletion

difftime object with the time needed for the estimation

version

the s6modelversion that produced the results

alko989/s6model documentation built on Nov. 2, 2023, 10:04 p.m.