r4ss (version 1.24.0)

addSSsummarize: Add a model to the list of models to compare

Description

Adds specified quantities from any model to the list of models returned from SSsummarize for further comparison.

Usage

addSSsummarize(origModels, newModels)

Arguments

origModels

A list of models created by SSsummarize.

newModels

A list of models to add to the originals models list. Each new model is an element of the list, and is a list itself with possible components described in the details below.

Value

Returns list as is returned from SSsummarize, but contains additions for the new models.

See Also

SSsummarize SSplotComparisons

Examples

# NOT RUN {
  
# }
# NOT RUN {
  ######################################
  #DO NOT RUN
tinss1 <- list(npars=A$fit$npar,maxgrad=A$fit$maxgrad,nsexes=1,
               #note, there is an estimated parameter called sd_sbt,
               #      but it is a single value
               SpawnBio=data.frame(c(1964,1965,A$yrs),
                                   c(A$sbo,A$sbo,A$sbt)*1e6,0,
                                   qnorm(0.025,c(A$so,A$so,A$sbt)*1e6,0),
                                   qnorm(0.975,c(A$so,A$so,A$sbt)*1e6,0)),
               Bratio=data.frame(A$yrs,A$sbt/A$sbo,0,
                                 qnorm(0.025,A$sbt/A$sbo,0),
                                 qnorm(0.975,A$sbt/A$sbo,0)),
               SPRratio=data.frame(A$yr,A$spr,0,qnorm(0.025,A$spr,0),
                                   qnorm(0.975,A$spr,0)),
               recruits=data.frame(A$yr,A$nt[,1]*1e6,0,qnorm(0.025,A$nt[,1]*1e5,0),
                                   qnorm(0.975,A$nt[,1]*1e6,0)),
               #I'm not sure exactly what wt are,
               #   but it is important to line them up correctly
               recdevs=data.frame(A$recYrs,A$wt),  
               indices = data.frame(A$iyr,1e6*A$yt,1e6*A$qbt,
                                    rep(A$q,length(A$iyr)),rep(0.4,length(A$iyr)),
                                    rep(0,length(A$iyr)),rep(1,length(A$iyr)))
               )
  tinss <- list(tinss1,tinss1)   #can add more models here


  #add TINSS model to SS models already summarized                
  SSnTINSS <- addSSsummarize(models,tinss)
  mcmcInd <- seq(burnin+1,nrow(A$mc.sbt),thin)
  SSnTINSS$mcmc[[2]] <- data.frame(A$mc.sb0[mcmcInd],
                                   A$mc.sbt[mcmcInd,],
                                   A$mc.depl[mcmcInd,],
                                   A$mc.spr[mcmcInd,],
                                   A$mc.rt[mcmcInd,],
                                   log(A$mcmc[mcmcInd,"Ro"]*1e6),
                                   A$mcmc[mcmcInd,"msy"]*1e6)  
  names(SSnTINSS$mcmc[[2]]) <-
    c("SPB_Virgin",paste("SPB",A$yrs,sep="_"),
      paste("Bratio",A$yrs,sep="_"),
      paste("SPRratio",A$yr,sep="_"),
      paste("Recr",A$yr,sep="_"),"SR_R0","TotYield_MSY")
  modelnames <- c("SS", "TINSS","TINSS.MLE")
  
  SSplotComparisons(SSnTINSS, legendlabels=modelnames,
                    subplot=2,endyr=2011,mcmcVec=c(T,T,F))
  title(main="MCMC")
  SSplotComparisons(SSnTINSS, legendlabels=modelnames,
                    subplot=4,endyr=2011,mcmcVec=c(T,T,F))
  title(main="MCMC")
  ###############################################
  
# }
# NOT RUN {
# }