selectCC: selectCC conducts a selectivity enhanced catch curve analysis

In haddonm/datalowSA: A Package to Faciliate Application of Data poor Stock Assessments

selectCC conducts a selectivity enhanced catch curve analysis

Description

selectCC encapsulates the routines required to fit a selectivity enhanced catch curve to a catch-at-age composition sample. The method is described in Wayte, S.E. and N.L. Klaer (2010) An effective harvest strategy using improved catch-curves. Fisheries Research 106: 310-320. Although the log-likelihood used here is based on the strict multinomial distribution.

Usage

selectCC(M, maxage, counts, pars, plot = FALSE)

Arguments

M	the natural mortality estimate
maxage	is the maximum age in the available data
counts	is the numbers at age, a vector of counts with names that are the ages to which the counts relate
pars	three values in a vector, these are the initial estimates of the two selectivity parameters (A50, the age at 50 (A95 - A50), of course delta must be positive), and the initial estimate (guess) of the fishing mortality. See the example below.
plot	a logical parameter determining whether to plot the result or not, the default is FALSE

Value

a list containing the output from optim, 'best', with the parameter estimates and the other diagnostics from the fit, and a matrix, 'result' containing the observed and predicted values and counts

Examples

## Not run: 
M <-  0.6
ages <- 0:9
counts <- c(3,4,501,2531,936,233,76,17,5,1)
names(counts) <- 0:9
pars <- c(A50=2.5,delta=0.5,fcur=0.6)
selectCC(M,max(ages),counts,pars)
# now with a plot
selectCC(M,max(ages),counts,pars,plot=TRUE)

## End(Not run)  

haddonm/datalowSA documentation built on Nov. 5, 2023, 6:40 p.m.