simulate-methods: Simulation methods for SCA

In flr/FLa4a: A Simple and Robust Statistical Catch at Age Model

Simulation methods for SCA

Description

Simulation methods for a4a stock assessment fits.

Usage

simulate(object, nsim = 1, seed = NULL, ...)

## S4 method for signature 'a4aFitSA'
simulate(object, nsim = 1, seed = NULL, empirical = TRUE)

## S4 method for signature 'SCAPars'
simulate(object, nsim = 1, seed = NULL, empirical = TRUE)

## S4 method for signature 'a4aStkParams'
simulate(object, nsim = 1, seed = NULL, empirical = TRUE)

## S4 method for signature 'submodels'
simulate(object, nsim = 1, seed = NULL, empirical = TRUE)

## S4 method for signature 'submodel'
simulate(object, nsim = 1, seed = NULL, empirical = TRUE)

Arguments

object	object of relevant class (see signature of method)
nsim	number of iterations
seed	numeric with random number seed
...	additional argument list that might never be used
empirical	logical, shall the empirical method in MASS be used

Examples

data(ple4)
data(ple4.index)
fmodel <- ~factor(age) + factor(year)
qmodel <- list(~factor(age))
fit1 <-  sca(fmodel=fmodel, qmodel=qmodel, stock=ple4, indices=FLIndices(ple4.index))
fit1
summary(fit1)
stock.n(fit1)

flr/FLa4a documentation built on June 4, 2023, 11:05 a.m.