MSEtool (version 1.1.0)

SP: Surplus production model with UMSY and MSY as leading parameters

Description

A surplus production model that estimates the TAC using a time-series of catches and a relative abundance index and coded in TMB. The model is conditioned on catch and estimates a predicted index. The state-space version estimates annual deviates in biomass.

Usage

SP(x = 1, Data, rescale = "mean1", start = NULL, fix_dep = TRUE,
  fix_n = TRUE, silent = TRUE, opt_hess = FALSE,
  n_restart = ifelse(opt_hess, 0, 1), control = list(iter.max = 5000,
  eval.max = 10000), ...)
SP_SS(x = 1, Data, rescale = "mean1", start = NULL, fix_dep = TRUE,
  fix_n = TRUE, fix_sigma = TRUE, fix_tau = TRUE, early_dev = c("all",
  "index"), integrate = FALSE, silent = TRUE, opt_hess = FALSE,
  n_restart = ifelse(opt_hess, 0, 1), control = list(iter.max = 5000,
  eval.max = 10000), inner.control = list(), ...)

Arguments

x

An index for the objects in Data when running in closed loop simulation. Otherwise, equals to 1 When running an assessment interactively.

Data

An object of class Data.

rescale

A multiplicative factor that rescales the catch in the assessment model, which can improve convergence. By default, "mean1" scales the catch so that time series mean is 1, otherwise a numeric. Output is re-converted back to original units.

start

Optional list of starting values. See details.

fix_dep

Logical, whether to fix the initial depletion (ratio of biomass to carrying capacity in the first year of the model). If TRUE, uses the value in start, otherwise equal to 1 (assumes virgin conditions).

fix_n

Logical, whether to fix the exponent of the production function. If TRUE, uses the value in start, otherwise equal to n = 2, where the biomass at MSY is half of carrying capacity.

silent

Logical, passed to MakeADFun, whether TMB will print trace information during optimization. Used for dignostics for model convergence.

opt_hess

Logical, whether the hessian function will be passed to nlminb during optimization (this generally reduces the number of iterations to convergence, but is memory and time intensive and does not guarantee an increase in convergence rate). Ignored if integrate = TRUE.

n_restart

The number of restarts (calls to nlminb) in the optimization procedure, so long as the model hasn't converged. The optimization continues from the parameters from the previous (re)start.

control

A named list of parameters regarding optimization to be passed to nlminb.

...

Additional arguments (not currently used).

fix_sigma

Logical, whether the standard deviation of the index is fixed. If TRUE, sigma is fixed to value provided in start (if provided), otherwise, value based on Data@CV_Ind.

fix_tau

Logical, the standard deviation of the biomass deviations is fixed. If TRUE, tau is fixed to value provided in start (if provided), otherwise, equal to 1.

early_dev

Character string describing the years for which biomass deviations are estimated in SP_SS. By default, deviations are estimated in each year of the model ("all"), while deviations could also be estimated once index data are available ("index").

integrate

Logical, whether the likelihood of the model integrates over the likelihood of the biomass deviations (thus, treating it as a state-space variable).

inner.control

A named list of arguments for optimization of the random effects, which is passed on to newton via MakeADFun.

Value

An object of '>Assessment containing objects and output from TMB.

Functions

• SP: Fixed effects model

• SP_SS: State-space version

Required Data

• SP: Cat, Ind

• SP_SS: Cat, Ind

Optional Data

SP_SS: CV_Ind

Details

To provide starting values for the SP, a named list can be provided for UMSY, MSY, dep, and n via the start argument (see example).

For SP_SS, a start value can also be provided for sigma and tau, the standard deviation of the index and log-biomass deviates, respectively. Deviations are estimated beginning in the year when index data are available.

References

Fletcher, R. I. 1978. On the restructuring of the Pella-Tomlinson system. Fishery Bulletin 76:515:521.

Pella, J. J. and Tomlinson, P. K. 1969. A generalized stock production model. Inter-Am. Trop. Tuna Comm., Bull. 13:419-496.

See Also

SP_production

plot,Assessment,ANY-method summary,Assessment-method retrospective profile_likelihood make_MP

Examples

# NOT RUN {
data(swordfish)

#### Observation-error surplus production model
res <- SP(Data = swordfish)

# Provide starting values, assume B/K = 0.95 in first year of model
# and symmetrical production curve (n = 2)
start <- list(UMSY = 0.1, MSY = 1e5, dep = 0.95, n = 2)
res <- SP(Data = swordfish, start = start)

#### State-space version
res <- SP_SS(Data = swordfish, start = list(dep = 0.95, tau = 0.3),
fix_sigma = TRUE)
# }