SepVPA-methods: Separable Virtual Population Analysis in FLR

In flr/FLAssess: Generic Classes and Methods for Stock Assessment Models

Separable Virtual Population Analysis in FLR

Description

Performs Separable Virtual Population Analysis. Methods for function SepVPA in package in Package ‘FLAssess’. Requires an object of class FLSepVPA.control to be created.

Methods

SepVPA<-function(stock, control=FLSepVPA.control(), ref.harvest="missing", fratio="missing", fit.plusgroup=TRUE, desc="",...)

, where stock is of type FLStock, control is of type FLSepVPA.control(), ref.harvest and fratio are numeric and fit.plusgroup is Boolean.

Examples

# Example based on ple4 dataset
data(ple4)
# Set up stock with correct dimensions
my.stock <- FLStock(catch.n(ple4))
my.stock@range["plusgroup"] <- 15
#load catch data and mortality
my.stock@catch.n <- ple4@catch.n
my.stock@catch.n[my.stock@catch.n==0] <- 1
my.stock@m <- ple4@m
my.control <- FLSepVPA.control(sep.age = 5)
# Set up in final year
my.stock@stock.n[,"2001"] <- ple4@stock.n[,"2001"]
# Run SepVPA
my.stock.SepVPA <- SepVPA(my.stock, my.control, fit.plusgroup=TRUE)

flr/FLAssess documentation built on Sept. 9, 2022, 9:54 p.m.