Set up biological inputs for the estimation model

Populates input_list with biological arrays and parameter structures needed by the TMB/RTMB objective function: weight-at-age (spawning, fishery, and survey), maturity-at-age, ageing error, the size-age transition matrix (optional), small constants for numerical stability, and the natural mortality block structure and mapping. Called after Setup_Mod_Dim.

Usage

Setup_Mod_Biologicals(
  input_list,
  WAA,
  WAA_fish = NULL,
  WAA_srv = NULL,
  MatAA,
  addtocomp = NULL,
  comp_const_obs = NULL,
  addtofishidx = NULL,
  addtosrvidx = NULL,
  addtotag = NULL,
  AgeingError = NULL,
  AgeingError_fish = NULL,
  AgeingError_srv = NULL,
  Use_M_prior = 0,
  M_prior = NA,
  fit_lengths = 0,
  SizeAgeTrans = NA,
  SizeAgeTrans_fish = NULL,
  SizeAgeTrans_srv = NULL,
  do_caal = 0,
  growth_model = "none",
  growth_spec = "est_all",
  growth_fix = NULL,
  growth_tv_model = NULL,
  growth_tv_years = NULL,
  growth_tv_link = "log",
  growth_par_bounds = NULL,
  growth_tv_sigma_spec = "fix",
  growth_tv_spec = "est_all",
  growth_tv_type = "curve",
  growth_rw_init_sigma = 5,
  growth_semipar = "none",
  growth_semipar_spec = "fix",
  growth_semipar_ages = NULL,
  growth_semipar_years = NULL,
  LenBinMap = NULL,
  growth_A1 = NULL,
  growth_A2 = NULL,
  growth_len_lower = NULL,
  growth_L0 = NULL,
  growth_cv_type = "len",
  growth_sd_type = "cv",
  growth_dist = "normal",
  growth_plus_group = "mixture",
  waa_model = "data",
  wt_len_pars = NULL,
  M_spec = "est_ln_M",
  M_popblk_spec = "constant",
  M_ageblk_spec = "constant",
  M_regionblk_spec = "constant",
  M_yearblk_spec = "constant",
  M_seasblk_spec = "constant",
  M_sexblk_spec = "constant",
  Fixed_natmort = NULL,
  NAA_re = "none",
  NAA_re_ages = NULL,
  NAA_re_years = NULL,
  NAA_re_seasons = "annual",
  NAA_re_season = "iid",
  NAA_re_season_spec = "est_all",
  NAA_re_where = NULL,
  NAA_pe_spec = "est_all",
  NAA_sigma_spec = "est",
  NAA_re_region = "iid",
  NAA_re_region_spec = "est_all",
  NAA_re_pop = "iid",
  NAA_re_sex = "iid",
  NAA_sigma_popblk_spec = "constant",
  NAA_sigma_regionblk_spec = "constant",
  NAA_sigma_yearblk_spec = "constant",
  NAA_sigma_seasblk_spec = "constant",
  NAA_sigma_ageblk_spec = "constant",
  NAA_sigma_sexblk_spec = "constant",
  ...
)

Arguments

input_list

Named list with $data, $par, $map, and $verbose sublists, as returned by Setup_Mod_Dim.

WAA

Numeric array of spawning weight-at-age with dimensions [n_pop × n_regions × n_years × n_seas × n_ages × n_sexes]. Used to compute spawning stock biomass. Also serves as the fallback for WAA_fish and WAA_srv when those are NULL.

WAA_fish

Numeric array of fishery weight-at-age with dimensions [n_pop × n_regions × n_years × n_seas × n_ages × n_sexes × n_fish_fleets]. If NULL (default), WAA is broadcast across all fishery fleets.

WAA_srv

Numeric array of survey weight-at-age with dimensions [n_pop × n_regions × n_years × n_seas × n_ages × n_sexes × n_srv_fleets]. If NULL (default), WAA is broadcast across all survey fleets.

MatAA

Numeric array of maturity-at-age proportions ($\in [0,1]$) with dimensions [n_pop × n_regions × n_years × n_seas × n_ages × n_sexes]. When rec_lag = 0 (age-0 recruitment, set via Setup_Mod_Rec), maturity at the recruit age (the first age class) must be exactly 0 for all populations, regions, years, seasons, and sexes, an error is raised otherwise. Requires Setup_Mod_Rec to have been called first so rec_lag is already set.

addtocomp

Deprecated here, pass it to Setup_Mod_Weighting instead, which now owns this constant along with every other likelihood weight. Still accepted for backward compatibility: if supplied, it is forwarded to Setup_Mod_Weighting with a message rather than applied here directly. (Small constant added to composition proportions before likelihood evaluation to avoid log(0); default 1e-3 in Setup_Mod_Weighting. Ignored when a logistic-normal likelihood is specified, as that family handles zeros internally.)

comp_const_obs

Deprecated here, pass it to Setup_Mod_Weighting instead. Still accepted for backward compatibility (forwarded with a message). Integer switch (0 or 1) controlling where addtocomp is applied in the multinomial likelihood, not a constant to be tuned. 1 (default in Setup_Mod_Weighting) adds it to the observed proportions that weight the multinomial as well as inside the logarithms, so the likelihood is stationary exactly at pred = obs. 0 weights by the raw observed proportions. The Dirichlet-multinomial sanity check that used to read it here (inside Setup_Mod_FishIdx_and_Comps/ Setup_Mod_SrvIdx_and_Comps) now runs inside Setup_Mod_Weighting once the final value is known.

addtofishidx

Deprecated here, pass it to Setup_Mod_Weighting instead. Still accepted for backward compatibility (forwarded with a message). Small constant added to fishery indices; default 1e-4 in Setup_Mod_Weighting.

addtosrvidx

Deprecated here, pass it to Setup_Mod_Weighting instead. Still accepted for backward compatibility (forwarded with a message). Small constant added to survey indices; default 1e-4 in Setup_Mod_Weighting.

addtotag

Deprecated here, pass it to Setup_Mod_Weighting instead. Still accepted for backward compatibility (forwarded with a message). Small constant added to tag recovery observations; default 1e-10 in Setup_Mod_Weighting.

AgeingError

Ageing error (age-age transition) array mapping true modeled ages to observed age bins. Each row is one model age's share across the observed bins and sums to one, or to zero to drop that model age from the observations. This is the age-axis twin of LenBinMap: the likelihood applies the two identically and validates them identically, so read either one for the other. It changes which bins the compositions are recorded on; to leave observed bins out of the likelihood without changing the bins themselves, use the *_bins arguments instead. Accepted forms:

2D matrix [n_model_ages × n_obs_ages]: Time-invariant ageing error; replicated internally across all years.
3D array [n_years × n_model_ages × n_obs_ages]: Time-varying ageing error.
NULL (default): An identity matrix is constructed, assuming modeled and observed age bins are identical. If observed bins are a subset of modeled ages (e.g., observed ages 2-10 vs. modeled ages 1-10), supply a shifted identity matrix such as diag(1, n_model_ages)[, obs_age_index] to avoid a dimensional mismatch.

AgeingError_fish

Optional fleet-specific ageing error for the fishery fleets, for when the fleets do not read ages the same way. Accepted forms: a 3D array [n_model_ages × n_obs_ages × n_fish_fleets] for a time-invariant matrix per fleet, a 4D array [n_years × n_model_ages × n_obs_ages × n_fish_fleets] for a time-varying one, or NULL (default), which gives every fishery fleet the shared AgeingError. Each fleet's slice is validated the same way AgeingError is, and every fleet must land on the same observed age bins, since the observed composition arrays have one age dimension shared across fleets.

AgeingError_srv

Optional fleet-specific ageing error for the survey fleets, in the same forms as AgeingError_fish, with n_srv_fleets in place of n_fish_fleets. NULL (default) gives every survey fleet the shared AgeingError.

Use_M_prior

Integer flag to apply a lognormal prior on natural mortality. 0 = no prior (default); 1 = apply prior.

M_prior

Data frame of prior hyperparameters for natural mortality, with one row per unique block combination. Required columns:

popblk, regionblk, yearblk, ageblk, sexblk: Block indices identifying which parameter the prior applies to.
mu: Prior mean in natural (untransformed) space.
sd: Prior standard deviation.
seasblk: Optional season block index. Left out, it reads the block covering season one, which is every season unless M_seasblk_spec splits them.

Example for a single shared prior:

M_prior <- data.frame(
  popblk = 1, regionblk = 1, yearblk = 1,
  ageblk = 1, sexblk = 1,
  mu = 0.085, sd = 0.05
)

Only used when Use_M_prior = 1.

fit_lengths

Integer flag for fitting length compositions. 0 = no (default); 1 = yes. Requires a valid SizeAgeTrans array.

SizeAgeTrans

Numeric array of size-at-age transition probabilities (column-stochastic; each age column sums to 1) with dimensions [n_pop × n_regions × n_years × n_seas × n_lens × n_ages × n_sexes]. Required when fit_lengths = 1; ignored otherwise. The shared key every fleet reads unless SizeAgeTrans_fish/SizeAgeTrans_srv override it for that fleet type.

SizeAgeTrans_fish, SizeAgeTrans_srv

Optional per-fleet size-at-age transition arrays, dimensioned like SizeAgeTrans with an added trailing fleet dimension (n_fish_fleets/n_srv_fleets). NULL (default) reads every fleet's key from the shared SizeAgeTrans. Only meaningful with growth_model = "none"; a growth model already derives one key per fleet, at that fleet's own timing, and rejects these to avoid mixing two sources for the same key. This is the fixed-data counterpart of Setup_Sim_Biologicals's SizeAgeTrans_fish_input/SizeAgeTrans_srv_input, and of WAA_fish/WAA_srv overriding the shared WAA.

do_caal

Integer flag for building the joint arrays at length and age. 0 = no (default); 1 = yes. Requires fit_lengths = 1. Turning this on adds Fish_caal, Fish_caal_discard and Srv_caal to the report, holding predicted retained catch, discards and survey index jointly by length and age.

growth_model

Character. "none" (default) keeps SizeAgeTrans and the weight-at-age arrays as data. "vb_schnute" builds the size-age transition from estimable von Bertalanffy parameters in Schnute's form: length L1 at reference age growth_A1, length L2 at growth_A2, rate K, and CVs of length at age CV1 and CV2 at the two reference ages. Growth below growth_A1 is linear from growth_L0 at age zero, the CV interpolates between the two references, and the plus group has an adjustment for fish older than the accumulator age. "richards" is the same curve with a sixth parameter, the Richards coefficient rho, applied to the lengths raised to that power (rho = 1 recovers the von Bertalanffy form). Requires fit_lengths = 1; SizeAgeTrans is then ignored and may be NA.

growth_spec

Character. How the growth parameters are estimated: "est_all" (default, one set per population, region and sex), "est_shared_r" (shared across regions), "est_shared_s" (shared across sexes), "est_shared_r_s" (one set per population), or "fix".

growth_fix

Logical vector, one entry per growth parameter, naming which of L1, L2, K, CV1, CV2 (and rho) stay at their starting values whatever growth_spec says.

growth_tv_model

Time variation of the growth parameters. NULL (default) holds every parameter constant. Otherwise a character vector naming a structure per parameter, either of length n_gpars in the parameter order or named by parameter (L1, L2, K, CV1, CV2, rho) with the rest constant, each one of "none", "iid" (independent annual deviations) or "rw" (a random walk). A varying parameter gets a deviation series ln_growth_devs and a log sigma in the first data source of growth_pe_pars.

growth_tv_years

Years the deviations are active in, calendar years. NULL (default) for every model year, a vector applied to every varying parameter, or a list named by parameter. Deviations outside the range are kept at zero.

growth_tv_link

Character, the scale a deviation enters on. "log" (default) multiplies the parameter by $e^{\delta}$; "logit" keeps it inside growth_par_bounds, $P_y = lo + (hi - lo)\,\mathrm{logit}^{-1}(\mathrm{logit}((P - lo)/(hi - lo)) + \delta_y)$, so the parameter approaches a bound however large the deviation instead of crossing it.

growth_par_bounds

Matrix [n_gpars x 2] of lower and upper bounds, natural scale, required under the logit link.

growth_tv_sigma_spec

Character, "fix" (default) holds the process error standard deviations of the deviations at their starting values, "est" estimates them. Both read the first data source of growth_pe_pars, one slot per growth parameter.

growth_tv_spec

Character, how the deviations are shared across strata, with the same vocabulary as growth_spec: "est_all" (default), "est_shared_r", "est_shared_s" or "est_shared_r_s".

growth_tv_type

Character. "curve" (default) reads every year's size at age off that year's curve. "cohort" has size at age forward cohort by cohort: each year every cohort grows by the increment the current year's parameters imply from the size it reached, ages still in the linear phase keep the length at growth_A1 their birth year's parameters gave them, the first age past growth_A1 is placed on the current year's curve, and the plus group's size blends the cohort entering it with the fish already there by their numbers at age. The CV at age is then kept at the first year's sizes. The propagation starts in the first year any deviation is active; every earlier year sits on the first year's curve.

growth_rw_init_sigma

Standard deviation given to the first year of a random walk on a growth parameter, as srvsel_rw_init_sigma for selectivity. Default 5.

growth_semipar

Character. Semi-parametric growth: a year-by-age surface of deviations on mean length at age, multiplying the parametric curve, so the curve stays the parametric part and the deviations hold departures from it. "none" (default) keeps growth purely parametric; otherwise one of "iid", "rw" (a random walk over years within an age), "3dmarg" or "3dcond" (a three-dimensional Gaussian Markov random field over age, year and cohort, on the marginal or conditional variance), or "2dar1" (a separable first-order autoregression over ages and years). The same process error forms the selectivity deviations use, so a growth surface and a selectivity surface are penalized the same way. The spread at age follows the deviated mean, which leaves the coefficient of variation at age to the parametric part.

growth_semipar_spec

Character, whether the second data source of growth_pe_pars is estimated. Whether the process error hyperparameters are estimated ("est") or kept at their starting values ("fix", the default). The deviations themselves are always estimated.

growth_semipar_ages

Ages the deviations are estimated over, as ages (not indices). NULL (default) uses every age. Ages outside the set are kept at zero, which is how a surface is restricted to the ages the length data actually inform.

growth_semipar_years

Years the deviations are estimated over, calendar years. NULL (default) uses every year.

LenBinMap

Optional matrix [n_lens x n_obs_lens] mapping the model's length bins onto the bins the length compositions are recorded on, for compositions on coarser bins than the model has (a population of 1 cm bins fit to 5 cm compositions, say). Observed length compositions are then dimensioned by n_obs_lens and the expected compositions are mapped through it inside the likelihood. This is the length-axis twin of AgeingError: the likelihood applies the two identically and validates them identically, so read either one for the other. Each row is one model bin's share across the observed bins and sums to one, or to zero to drop that model bin from the observations. It changes which bins the compositions are recorded on; to leave observed bins out of the likelihood without changing the bins themselves, use the *LenComps_bins arguments instead. NULL (default) fits the compositions on the model bins.

growth_A1, growth_A2

Reference ages for L1 and L2. growth_A2 = "Linf" instead makes L2 the asymptotic length itself, with no second reference age to solve it from.

growth_len_lower

Numeric vector of the lower edges of the length bins. lens in Setup_Mod_Dim are bin midpoints; the key is built on the edges.

growth_L0

Length at age zero anchoring the linear phase. Defaults to growth_len_lower[1].

growth_cv_type

Character, "len" (default) interpolates the CV on mean length between L1 and L2, "age" on age.

growth_sd_type

Character, "cv" (default) scales the mean by the CV parameters, "sd" reads them as standard deviations.

growth_dist

Character, "normal" (default) or "lognormal" distribution of length at age.

growth_plus_group

Character. "mixture" (default) takes the plus group's mean length as the survivorship-weighted mixture of the ages it holds, their numbers declining at an assumed 0.2 per year and their length rising from the curve at the accumulator age to the asymptote; "curve" reads the curve at the accumulator age.

waa_model

Character. Where weight at age comes from. "data" (default) reads WAA, WAA_fish and WAA_srv from the arguments of the same name. "wt_len" builds them from the size-age key and the weight-length relationship $W = a L^b$ applied at the bin midpoints, so weight at age holds the spread of length at age rather than being the weight of the mean length; the spawning weight uses the key at spawning time and each fleet's weight the key at that fleet's timing, t_fish or t_srv. Under "wt_len", WAA may be NULL, and reference point and projection code still read data$WAA, so copy the reported arrays into the data list before calling them.

wt_len_pars

Weight-length parameters $a, b$ in $W = a L^b$, a vector of two or an array [n_pop x n_regions x n_sexes x 2]. Required when waa_model = "wt_len".

M_spec

Character string controlling natural mortality estimation. One of:

"est_ln_M" (default): Estimate ln_M across the defined blocks.
"fix": Fix mortality to Fixed_natmort; ln_M parameters are mapped to NA and not passed to the optimizer.

M_popblk_spec

Blocking structure for ln_M across populations. Either "constant" (default; single shared value) or a list of integer index vectors defining population groups, e.g., list(1, 2) for population-specific M.

M_ageblk_spec

Blocking structure across ages. Either "constant" (default) or a list of integer index vectors, e.g., list(1:5, 6:10).

M_regionblk_spec

Blocking structure across regions. Either "constant" (default) or a list of integer index vectors, e.g., list(1:3, 4:5).

M_yearblk_spec

Blocking structure across years. Either "constant" (default) or a list of integer index vectors, e.g., list(1:10, 11:30).

M_seasblk_spec

Blocking structure across seasons. Either "constant" (default, one rate all year) or a list of integer index vectors, e.g. list(1, 2) for a rate in each of two seasons, or list(1:2, 3:4) to split a four season year in half. Blocks hold rates per year, so two half-year seasons at 0.2 and 0.4 accumulate 0.1 and 0.2, an annual 0.3. A rate is not a share. "constant" is numerically identical to a model built before seasonal M existed.

Only identifiable off within-year data: seasonal catch, seasonal comps, or surveys in more than one season. Without those it trades against seasonal selectivity and the F devs. Even with them the annual total comes back much better than the split, so prefer fixing the split and estimating the level. Warns if season blocks are given for a single season model.

M_sexblk_spec

Blocking structure across sexes. Either "constant" (default; shared across sexes) or a list of integer index vectors, e.g., list(1, 2) for sex-specific M.

Fixed_natmort

Numeric array of fixed natural mortality, either [n_pop × n_regions × n_years × n_ages × n_sexes] or the same with n_seas between years and ages. The 5d form is expanded across seasons, so old scripts still work. Values are rates per year either way, not pre-apportioned amounts: mortality in a season is the rate times seasdur. Required when M_spec = "fix", ignored otherwise.

NAA_re

Character. State-space numbers at age: the log numbers become parameters for ages two and older, including the plus group, and the deterministic mortality and ageing step becomes the prediction they are penalized against. One of "none" (default, numbers stay deterministic), "iid", "1dar1_a" (autoregression over ages), "1dar1_y" (over years), "2dar1" (separable over both), or "3dcond" and "3dmarg" (a Gaussian Markov random field over age, year and cohort, on the conditional or the marginal variance).

Age one belongs to ln_RecDevs and year one at ages two and older to ln_InitDevs, so the three partition the numbers at age rather than overlapping. Which cells are estimated is set by map$ln_NAA and data$n_est_naa_re, never by dim(ln_NAA). The state covers the assessment years only: Do_Population_Projection advances projected numbers deterministically, so a forecast omits this process error, while the closed loop operating model does project the state forward.

NAA_re_ages

Ages the state is estimated over, matched against input_list$data$ages by value, not by position. A model whose ages are 0:4 therefore takes NAA_re_ages = c(1, 2, 3, 4) for the full state, and c(0, 1, 2, 3) is an error because age 0 is the first age. NULL (default) uses ages[-1]. Must be a contiguous run: the state is penalized as one rectangular slice, so a gap would leave penalized cells the dynamics never wrote.

NAA_re_years

Calendar years the state is estimated over, matched against input_list$data$years by value, not by position, so a model starting in 1983 takes 1984 and not 2 for its first state year. NULL (default) uses years[-1]. Must be a contiguous run.

NAA_re_seasons

Seasons the state is estimated over. "annual" (the default) puts a state at season one only, so the numbers within a year stay deterministic and the state is a purely annual innovation, which is what the model did before seasons were an option. "all" puts one at the start of every season. An integer vector of season indices selects specific seasons, and unlike NAA_re_ages and NAA_re_years it need not be contiguous: the season dim is only ever independent or unstructured, neither of which reads adjacency. That is the argument to use when only some seasons have observations, since a season with no data returns its prior as its posterior. The age, year and cohort correlations in NAA_pe_pars have no season dim, so every active season shares them within a population, region and sex; the standard deviation is what varies by season, through NAA_sigma_seasblk_spec.

NAA_re_season

Character. Correlation across seasons within a year, composed with the other dims the same way. "iid" (the default) leaves the seasonal innovations independent; "us" estimates an unstructured correlation, $n_k(n_k-1)/2$ parameters over the $n_k$ active seasons. Needs more than one active season.

NAA_re_season_spec

Character controlling how the season correlations are shared, taking the same values as NAA_re_region_spec.

NAA_re_where

Integer matrix [population, region], 1 where the numbers at age state runs and 0 where a population never occupies that region. NULL (default) gives every cell a state. A natal homing population that never reaches a region holds no fish there, so a lognormal state on that cell is undefined and the penalty would take the logarithm of zero. Cells set to 0 are dropped from the map as well as from the penalty, and they need the region and population correlations off.

NAA_pe_spec

Character controlling how the age, year and cohort correlations in NAA_pe_pars are shared, following the package's spec strings. "est_all" (the default) gives a free set per population, region and sex, which for a three region model under "2dar1" is six correlations. "est_shared_p", "est_shared_r" and "est_shared_s" share one dim, "est_shared_p_r", "est_shared_p_s" and "est_shared_r_s" share two, and "est_shared_p_r_s" gives one set for the whole model. "fix" holds them all at their starting values, which is zero correlation unless NAA_pe_pars is passed through starting_values. Sharing a correlation is not the same as correlating the innovations: regions that share $\rho$ still get independent shocks, whereas NAA_re_region = "us" makes the shocks themselves covary. Sharing never changes which cells are estimated, only how many hyperparameters they draw on.

NAA_sigma_spec

Character, whether the process error standard deviations are estimated ("est", the default) or kept at their starting values ("fix"). The states themselves are always estimated.

NAA_re_region

Character. Correlation across regions, composed with whatever NAA_re gives over the age and year grid. "iid" (the default) leaves regions independent; "us" estimates an unstructured correlation, $n_r(n_r-1)/2$ parameters, placing no shape on how regions covary. Independence is the default deliberately: a flexible correlation manufactures structure from independent data far more readily than it misses real structure.

NAA_re_region_spec

Character controlling how the region correlations are shared, following the package's spec strings: "est_all" (the default) gives a free correlation matrix per population and sex, "est_shared_p" and "est_shared_s" share it over one of those dims, "est_shared_p_s" gives a single matrix for the whole model, and "fix" holds them all.

NAA_re_pop, NAA_re_sex

Character. Correlation across populations and across sexes, composed with the region, age and year structures the same way. "iid" (the default) leaves them independent; "us" estimates an unstructured correlation. Both are global to the model rather than varying over the other dims, so a two-sex model spends exactly one parameter on NAA_re_sex = "us".

NAA_sigma_popblk_spec, NAA_sigma_regionblk_spec, NAA_sigma_yearblk_spec, NAA_sigma_seasblk_spec, NAA_sigma_ageblk_spec, NAA_sigma_sexblk_spec

Blocking for the process error standard deviation, each either "constant" (the default) or a list of integer vectors assigning indices to blocks, exactly as the M_*blk_spec arguments do. Blocking shares a standard deviation; it never removes a cell from the state. Only NAA_re = "iid" admits a standard deviation that varies over years or ages: every other form is separable or Markov in a dim, so it has one standard deviation per population, region and sex. The season dim is the exception, because it is whitened outside the age and year density: a season-varying standard deviation works under any NAA_re, and is ruled out only by NAA_re_season = "us", which needs one scale across the dim it correlates.

...

Optional starting value overrides passed by name. Currently recognized:

ln_M: Array of log-scale starting values for natural mortality, dimensioned [n_popblks × n_regionblks × n_yearblks × n_seasblks × n_ageblks × n_sexblks]. Defaults to log(0.5). A 5d array from an older script still works when there is one season block, same values in the same order.
ln_growth_pars: Array of log-scale starting values for the growth parameters, dimensioned [n_pop × n_regions × n_sexes × n_gpars] in the order L1, L2, K, CV1, CV2 and, under the Richards form, rho. Defaults to the ends of the length bins with a rate of 0.15 and CVs of 0.1, so supply your own for any real model.
growth_pe_pars: Array of process error starting values for both growth deviation data sources, dimensioned [n_pop × n_regions × max(4, n_ages, n_gpars) × n_sexes × 2]. The first data source holds one log sigma per growth parameter for the time-varying deviations; the second holds the semi-parametric surface's correlations by age, year and cohort in slots one to three and a log scale in slot four for the correlated forms, or one log sigma per age for "iid" and "rw". Defaults to log(0.1) for the first data source and log(0.05) with correlations of 0.3 for the second. Slots a form does not read are mapped off.

All ... arguments are silently ignored when M_spec = "fix".

Value

The input input_list with $data, $par, and $map sublists updated. Key additions include $data$WAA, $data$WAA_fish, $data$WAA_srv, $data$MatAA, $data$AgeingError, $data$M_blocks, $par$ln_M, and $map$ln_M.

Usage

Arguments

Value

See also