srrTMB: Fits Stock Recruitment Relationships (SRR) in TMB

In flr/FLSRTMB: FLSR in TMB

Fits Stock Recruitment Relationships (SRR) in TMB

Description

Fits Stock Recruitment Relationships (SRR) in TMB

Usage

srrTMB(object, ...)

## S4 method for signature 'FLSRs'
srrTMB(object, ...)

## S4 method for signature 'FLSR'
srrTMB(
  object,
  spr0 = "missing",
  s = NULL,
  s.est = TRUE,
  s.logitsd = 50,
  r0.pr = "missing",
  lplim = 0.01,
  uplim = 0.3,
  Blim = "missing",
  d = 1,
  d.est = TRUE,
  d.logitsd = 100,
  ld = 0.5,
  ud = 3,
  plim = lplim,
  pmax = uplim,
  nyears = NULL,
  report.sR0 = FALSE,
  inits = NULL,
  lower = NULL,
  upper = NULL,
  SDreport = TRUE,
  verbose = FALSE,
  rm.yrs = "missing",
  bias.correct = TRUE
)

Arguments

object	Input FLSR = as.FLSR(stock,model) object with current model options bevholtSV bevholtDa 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
Blim	fixing Blim, only works with segreg
d	depensation parameter (default = 1)
d.est	option to estimate depensation d
d.logitsd	priod sd for logit(d)
ld	lower bound of depensation parameter d
ud	upper bound of depensation parameter d
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
rm.yrs	remove recruitment years from model fit
bias.correct	if TRUE, bias correction of the uniform logistic hockey-stick prior for Blim/B0 (recommended)

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
do.call(rbind,lapply(srs,AIC))
# Bias-correction test for Hockey-Stick
srs=FLSRs(
 correct = srrTMB(as.FLSR(ple4,model=segreg),spr0=mean(spr0y(ple4)),lplim=0.001,uplim=0.08),
 bias =srrTMB(as.FLSR(ple4,model=segreg),spr0=mean(spr0y(ple4)),lplim=0.001,uplim=0.08,bias.correct=FALSE,s.logitsd=20))
plotsrs(srs,rel=TRUE)
# Depensation
d.srs = FLSRs(
uniform = srrTMB(as.FLSR(ple4,model=bevholtDa),spr0=spr0y(ple4)),
larger1 = srrTMB(as.FLSR(ple4,model=bevholtDa),spr0=spr0y(ple4),ld=1),
prior1 = srrTMB(as.FLSR(ple4,model=bevholtDa),spr0=spr0y(ple4),d=1.5,d.logitsd=1.5),
prior1.5 = srrTMB(as.FLSR(ple4,model=bevholtDa),spr0=spr0y(ple4),d=1.5,d.logitsd=1.5),
fixed1.5 = srrTMB(as.FLSR(ple4,model=bevholtDa),spr0=spr0y(ple4),d=1.5,d.est=FALSE),
fixed2.5 = srrTMB(as.FLSR(ple4,model=bevholtDa),spr0=spr0y(ple4),d=2.5,d.est=FALSE)
)
plotsrs(d.srs) 

flr/FLSRTMB documentation built on April 17, 2025, 11:02 a.m.