MQMF (version 0.1.0)

spmCE: spmCE - calculates the dynamics for nultiple cpue time-series

Description

spmCE calculates the dynamics using a Schaefer of Fox model and is used instead of spm when there are multiple index vectors. The outputs include predicted Biomass, year, catch, cpue, predicted cpue, contributions to q, ssq, and depletion levels. Generally it would be more sensible to use simpspm when fitting a Schaefer model and simpfox when fitting a Fox model as those functions are designed to generate only the predicted cpue required by the functions ssq and negLLM, but the example shows how it could be used.

Usage

spmCE(
  inp,
  indat,
  schaefer = TRUE,
  year = "year",
  cats = "catch",
  index = "cpue"
)

Arguments

inp

a vector of 2 or 3 model parameters (r,K) or (r,K,Binit), you would use the latter if it was suspected that the fishery data started after some initial depletion had occurred. Then there should be the same number of sigma values as tehre are cpue time-series

indat

a matrix with at least columns 'year', 'catch', and 'cpue'

schaefer

a logical value determining whether the spm is to be a simple Schaefer model (p=1) or approximately a Fox model (p=1e-08). The default is TRUE

year

the column name within indat containing the years

cats

the column name within indat containing the catches

index

the column name within indat containing the cpue.

Value

a list of five objects; outmat the matrix with the dynamics results, q catchability, msy the maximum sustainable yield, the parameter values, and sumout, which contains r, K, B0, msy, p, q, Depl, FinalB, and InitDepl

Examples

# NOT RUN {
 data(twoindex)
 fish <- as.matrix(twoindex)
 pars <- log(c(0.04,155000,0.4,0.3))
 bestSP <- nlm(f=negLLM,p=pars,funk=simpspmM,indat=fish,
             schaefer=TRUE,logobs=log(fish[,c("cpue1","cpue2")]),
             steptol=1e-06,harvpen=TRUE)
 outfit(bestSP)  # best fitting estimates
 getMSY(exp(bestSP$estimate))
# }