LIME: Length-based Integrated Mixed Effects (LIME) assessment model

In DLMtool/DLMextra: Additional OMs, Data, and Assessment functions for DLMtool and MSEtool

Description

A wrapper function for the LIME model, a stock assessment model designed for data-limited scenarios with length composition data and biological parameters. Optionally, catch or index abundance data can also be included. Catch data should be used in order to estimate stock biomass for output-based harvest control rules. A steepness value of one is used in typical applications. The reported FMSY reference point is a proxy using either spawning potential ratio or Fmax (from yield-per-recruit). The BMSY reference point is calculated using estimated mean recruitment and fishing at FMSY.

Usage

LIME(
  x = 1,
  Data,
  add_catch = FALSE,
  add_index = FALSE,
  ESS = 50,
  CAL_dist = c("mult", "Dirmult"),
  SigmaC = 0.2,
  SigmaI = 0.2,
  SigmaR = Data@sigmaR[x],
  SigmaF = 0.3,
  nseas = 1L,
  Fproxy = c("F40", "F30", "Fmax"),
  yind = expression(1:ncol(Data@Cat)),
  integrate = FALSE,
  run_LIME_args,
  control = list(iter.max = 2e+05, eval.max = 4e+05),
  inner.control = list(),
  ...
)

Arguments

x	An index for the objects in Data when running in runMSE. Otherwise, equals to 1 when running an assessment interactively.
Data	An object of class Data.
add_catch	Logical, whether to include catch data.
add_index	Logical, whether to include index data.
ESS	The maximum annual sample size of the length composition data.
CAL_dist	Whether the model uses a multinomial "mult" or Dirichlet-multinomial "Dirmult" likelihood for the length composition.
SigmaC	The standard deviation of the catch in the likelihood.
SigmaI	The standard deviation of the index in the likelihood.
SigmaR	The standard deviation of the recruitment deviates in the likelihood.
SigmaF	The standard deviation of the F random walk in the likelihood.
nseas	The number of season in the model. In high F situations, multi-seasons may be needed to model smooth length distributions.
Fproxy	How the FMSY proxy reference point is calculated. The default is F40%.
yind	Optional, vector of years for the model. A subset of the data will be taken instead of the full time series in the Data object.
integrate	Logical, whether recruitment deviates are random effects in the model (TRUE) or penalized effects (FALSE). FALSE by default.
run_LIME_args	A named list of additional arguments for run_LIME. Only arguments that are passed to format_input are used.
control	A named list of agruments for optimization to be passed to nlminb.
inner.control	A named list of arguments for optimization of the random effects, which is passed on to newton.
...	Additional arguments (not currently used).

Value

An object of Assessment containing assessment output.

Required Data

• LIME: Mort, L50, L95, CAL, CAL_bins, vbK, vbLinf, vbt0, wla, wlb, LenCV, sigmaR

Optional Data

• LIME: Cat, Ind

Note

This is a wrapper function intended for a DLMtool Data object. The LIME package can be downloaded from Github with devtools::install_github("merrillrudd/LIME").

Author(s)

Q. Huynh

References

Rudd, M.B., and Thorson, J.T. 2017. Accounting for variable recruitment and fishing mortality in length-based stock assessments for data-limited fisheries. Canadian Journal of Fisheries and Aquatic Sciences 75:1019-1035. https://doi.org/10.1139/cjfas-2017-0143

See Also

plot.Assessment summary.Assessment make_MP

Examples

library(MSEtool)
data(SimulatedData)

res <- LIME(Data = SimulatedData)
plot(res)
summary(res)

## Use additional LIME functions
output <- res@info
LIME::plot_LCfits(Inputs = output$Inputs, Report = output$Report)
LIME::plot_output(Inputs = output$Inputs, Report = output$Report, Sdreport = output$Sdreport)

## Create an MP that uses a F30% proxy and catch data
LIME_MP <- make_MP(DLMextra::LIME, HCR40_10, Fproxy = "F30", add_catch = TRUE)

DLMtool/DLMextra documentation built on May 19, 2020, 12:49 p.m.