simCAA: Simulate Catch-at-Age Data

In Blue-Matter/MSEtool: Management Strategy Evaluation Toolkit

Simulate Catch-at-Age Data

Description

CAA generated with either a multinomial or logistic normal observation model from retained catch-at-age array

Usage

simCAA(nsim, yrs, n_age, Cret, CAA_ESS, CAA_nsamp)

Arguments

nsim	Number of simulations
yrs	Number of years
n_age	Number of age classes
Cret	Retained Catch at age in numbers - array(sim, years, maxage+1)
CAA_ESS	CAA effective sample size. If greater than 1, then this is the multinomial distribution sample size. If less than 1, this is the coefficient of variation for the logistic normal distribution (see details).
CAA_nsamp	CAA sample size

Details

The logistic normal generates the catch-at-age sample by first sampling once from a multivariate normal distribution with the mean vector equal to the logarithm of the proportions-at-age and the diagonal of the covariance matrix is the square of the product of the CV and the log proportions (all off-diagonals are zero). The sampled vector is then converted to proportions with the softmax function and expanded to numbers (CAA_nsamp). This method allows for simulating fractional values in the catch-at-age matrix.

Value

CAA array

Blue-Matter/MSEtool documentation built on Nov. 7, 2024, 11:38 p.m.