Prepare input data and parameters for WHAM model

Prepares data and parameter settings for fit_wham, optionally using an ASAP3 data file read into R by read_asap3_dat. By default, this will set up a SCAA version like ASAP without any penalties or random effects. If any asap3, basic_info, catch_info, and index_info arguments are not provided, some respective arbitrary assumptions are made. The various options described below, such as NAA_re and selectivity, can still be used without the asap3 object.

prepare_wham_input(
  asap3 = NULL,
  model_name = "WHAM for unnamed stock",
  recruit_model = 2,
  ecov = NULL,
  selectivity = NULL,
  M = NULL,
  NAA_re = NULL,
  catchability = NULL,
  age_comp = NULL,
  move = NULL,
  L = NULL,
  F = NULL,
  catch_info = NULL,
  index_info = NULL,
  basic_info = NULL
)

Arguments

asap3: (optional) list containing data and parameters (output from read_asap3_dat)
model_name: character, name of stock/model
recruit_model: numeric, option to specify stock-recruit model (see details)
ecov: (optional) named list of environmental covariate data and parameters (see set_ecov for full details)
selectivity: (optional) list specifying selectivity options by block: models, initial values, parameters to fix, and random effects (see set_selectivity for full details)
M: (optional) list specifying natural mortality options: model, random effects, initial values, and parameters to fix (see set_M for full details)
NAA_re: (optional) list specifying options for random effect on numbers-at-age, initial numbers at age, and recruitment model (see set_NAA for full details)
catchability: (optional) list specifying options for priors and random effects on catchability (see set_q for full details)
age_comp: (optional) character or named list, specifies age composition model for fleet(s) and indices (see set_age_comp for full details)
move: (optional) list specifying movement/migration options for models with more than 1 region (see set_move for full details)
L: (optional) list specifying "extra" mortality options (see set_L for full details)
F: (optional) list specifying fishing mortality options (see set_F for full details)
catch_info: (optional) list specifying catch information (see set_catch for full details)
index_info: (optional) list specifying index informaiton (see set_indices for full details)
basic_info: (optional) list of basic population information for use when asap3 is not provided (see details)

Value

a named list with the following components:

data: Named list of data, passed to TMB::MakeADFun
par: Named list of parameters, passed to TMB::MakeADFun
map: Named list defining how to optionally collect and fix parameters, passed to TMB::MakeADFun
random: Character vector of parameters to treat as random effects, passed to TMB::MakeADFun
years: Numeric vector of years to fit WHAM model (specified in ASAP3 .dat file)
ages.lab: Character vector of age labels, ending with plus-group (specified in ASAP3 .dat file)
model_name: Character, name of stock/model (specified in call to prepare_wham_input)
log: list of character strings attempting to describe the input and what the model assumes.

Details

recruit_model specifies the stock-recruit model. See wham.cpp for implementation.

= 1: SCAA (without NAA_re option specified) or Random walk (if NAA_re$sigma specified), i.e. predicted recruitment in year i = recruitment in year i-1
= 2: (default) Random about mean, i.e. steepness = 1
= 3: Beverton-Holt
= 4: Ricker

Note: fit_wham allows fitting a SCAA model (NAA_re = NULL), which estimates recruitment in every year as separate fixed effect parameters, but in that case no stock-recruit function is estimated. A warning message is printed if recruit_model > 2 and NAA_re = NULL. If you wish to use a stock-recruit function for expected recruitment, choose recruitment deviations as random effects, either only age-1 (NAA_re = list(sigma="rec")) or all ages (NAA_re = list(sigma="rec+1"), "full state-space" model). See below for details on NAA_re specification.

ecov specifies any environmental covariate data and models. See set_ecov for full details.

selectivity specifies options for selectivity, to overwrite existing options specified in the ASAP data file. See set_selectivity for full details.

M specifies estimation options for natural mortality and can overwrite M-at-age values specified in the ASAP data file. See set_M for full details.

NAA_re specifies options for random effects on numbers-at-age (NAA, i.e. state-space model or not). See set_NAA for full details. If NULL, a traditional statistical catch-at-age model is fit.

catchability specifies options for catchability. See set_q for full details. If NULL and asap3 is not NULL, a single catchability parameter for each index is used with initial values specified in ASAP file. If both are NULL, initial catchabilities for all indices = 0.3.

move specifies options for movement if there are multiple regions. See set_move for full details.

age_comp specifies the age composition models for fleet(s) and indices. See set_age_comp for full details.

catch_info is an optional list of fishery catch information that can be used to set up these types of observations when there is no asap3 file given. See set_catch for full details. Useful for setting up an operating model to simulate population processes and observations. Also can be useful for setting up the structure of assessment model when asap3 has not been used.

index_info is an optional list of survey/index information that can be used to set up these types of observations when there is no asap3 file given. See set_indices for full details. Useful for setting up an operating model to simulate population processes and observations. Also can be useful for setting up the structure of assessment model when asap3 has not been used.

basic_info is an optional list of information that can be used to set up the population and types of observations when there is no asap3 file given. Particularly useful for setting up an operating model to simulate population processes and observations. Also can be useful for setting up the structure of assessment model when asap3 has not been used. The current options are:

$ages: integer vector of ages (years) with the last being a plus group
$years: integer vector of years that the population model spans.
$n_seasons: number of seasons within year.
$n_fleets: number of fishing fleets.
$fracyr_seasons: proportions of year for each season within year (sums to 1).
$F: matrix (length(years) x n_fleets) of annual fishing mortality rates for each fleet to initialize the model.
$waa: array ((n_fleets + n_indices + n_stocks) x length(years) x length(ages)) of annual weight at at age for each fleet, each index, and spawning biomass for each stock.
$maturity: array (n_stocks x length(years) x length(ages)) of annual maturity at age for estimating spawning biomass for each stock.
$fracyr_SSB: matrix (n_years x n_stocks) (1 or length(years)) of yearly proportions (0-1) of the year at which to calculate spawning biomass.
$spawn_seasons: vector (n_stocks) of seasons in which each stock spawns.
$spawn_regions: vector (n_stocks) of regions in which each stock spawns.
$NAA_where: array (n_stocks x n_regions x n_ages) of 0/1 indicating where individuals of each stock may exist on January 1 of each year.
$Fbar_ages: integer vector of ages to use to average F at age for reported "Fbar" across all fleets, by regions and by fleet.
$q: vector (length(n_indices)) of catchabilities for each of the indices to initialize the model.
$percentSPR: (0-100) percentage of unfished spawning biomass per recruit for determining equilibrium fishing mortality reference point
$percentFXSPR: (0-100) percentage of SPR-based F to use in projections.
$percentFMSY: (0-100) percentage of Fmsy to use in projections.
$XSPR_input_average_years: which years to average inputs to per recruit calculation (selectivity, M, WAA, maturity) for SPR-based reference points. Default is last 5 years (tail(1:length(years),5))
$XSPR_R_avg_yrs: which years to average recruitments for calculating SPR-based SSB reference points. Default is 1:length(years)
$XSPR_R_opt: 1(3): use annual R estimates(predictions) for annual SSB_XSPR, 2(4): use average R estimates(predictions). 5: use bias-corrected expected recruitment. For long-term projections, may be important to use certain years for XSPR_R_avg_yrs
$simulate_process_error: T/F vector (length = 9). When simulating from the model, whether to simulate any process errors for (NAA, M, selectivity, q, movement, unidentified mortality, q priors, movement priors, Ecov). Only used for applicable random effects.
$simulate_observation_error: T/F vector (length = 3). When simulating from the model, whether to simulate catch, index, and ecov observations.
$simulate_period: T/F vector (length = 2). When simulating from the model, whether to simulate base period (model years) and projection period.
$bias_correct_process: T/F. Perform bias correction of log-normal random effects for NAA.
$bias_correct_BRPs: T/F. Perform bias correction of analytic SSB/R and Y/R when there is bias correction of log-normal NAA. May want to use XSPR_R_opt = 5 for long-term projections.

If other arguments to prepare_wham_input are provided such as selectivity, M, and age_comp, the information provided there must be consistent with basic_info. For example the dimensions for number of years, ages, fleets, and indices.

Examples

if (FALSE) {
asap3 = read_asap3_dat("ex1_SNEMAYT.dat")
input = prepare_wham_input(asap3)
mod = fit_wham(input)

# no ASAP3 file, default parameter values and configuration
input = prepare_wham_input()
mod = fit_wham(input, fit = FALSE)
set.seed(8675309)
simdata = mod$simulate(complete=TRUE)
input$data = simdata
fit = fit_wham(input, do.osa = FALSE)
}

Prepare input data and parameters for WHAM model

Arguments

Value

Details

See also

Examples