Fits Stock Recruitment Relationships (SRR) in TBM

srrTMB(
  object,
  spr0 = "missing",
  s = NULL,
  s.est = TRUE,
  s.logitsd = 20,
  r0.pr = "missing",
  lplim = 0.001,
  uplim = 0.3,
  plim = lplim,
  pmax = uplim,
  nyears = NULL,
  report.sR0 = FALSE,
  inits = NULL,
  lower = NULL,
  upper = NULL,
  SDreport = TRUE,
  verbose = FALSE
)

Arguments

object

Input FLSR = as.FLSR(stock,model) object with current model options

bevholtSV
rickerSV
segreg
geomean

spr0

unfished spawning biomass per recruit from FLCore::spr0(FLStock)

s

steepness parameter of SRR (fixed or prior mean)

s.est

option to estimate steepness

s.logitsd

prior sd for logit(s), default is 1.4 (flat) if s.est = TRUE

r0.pr

option to condition models on r0 priors (NULL = geomean)

lplim

lower bound of spawning ratio potential SRP, default 0.0001

uplim

upper bound of plausible spawning ratio potential SRP , default 0.3

plim

depreciated plim = usrp

pmax

depreciated pmax = lsrp

nyears

yearMeans from the tail used to compute a,b from the reference spr0 (default all years)

report.sR0

option to report s and R0 instead of a,b

inits

option to specify initial values of log(r0), log(SigR) and logit(s)

lower

option to specify lower bounds of log(r0), log(SigR) and logit(s)

upper

option to specify upper bounds of log(r0), log(SigR) and logit(s)

SDreport

option to converge hessian and get vcov

verbose

if TRUE, it shows tracing

Value

A list containing elements 'FLSR', of class FLSR

Examples

data(ple4)
gm <- srrTMB(as.FLSR(ple4,model=geomean),spr0=mean(spr0y(ple4)))
bh <- srrTMB(as.FLSR(ple4,model=bevholtSV),spr0=spr0y(ple4))
ri <- srrTMB(as.FLSR(ple4,model=rickerSV),spr0=spr0y(ple4))
hs <- srrTMB(as.FLSR(ple4,model=segreg),spr0=spr0y(ple4),lplim=0.05,uplim=0.2)
srs = FLSRs(gm=gm,bh=bh,ri=ri,hs=hs) # combine
plotsrs(srs) 

plotsrts(srs)  # relative

plotsrs(srs[2:4],b0=TRUE) # through to B0

plotsrs(srs[2:4],b0=TRUE,rel=TRUE)  # relative

gm@SV # estimates
#>    s    sigmaR       R0       rho      B0
#> 1 NA 0.4827602 991110.1 0.4088983 5020664
do.call(rbind,lapply(srs,AIC))
#>        [,1]
#> gm 85.87597
#> bh 87.37908
#> ri 93.09520
#> hs 89.81315