Make list of parameters for RTMB

Sets up the list of parameters, map of parameters (see map argument in TMB::MakeADFun()), and identifies some random effects parameters based on the input data and some user choices on model configuration.

These functions provide a template for the parameter and map setup that can be adjusted for alternative configurations. check_parameters() checks whether custom made parameter lists are of the correct dimension.

Usage

make_parameters(
  MARSdata,
  start = list(),
  map = list(),
  est_mov = c("none", "dist_random", "gravity_fixed"),
  silent = FALSE,
  ...
)

make_map(
  p,
  MARSdata,
  map = list(),
  est_M = FALSE,
  est_h = FALSE,
  est_mat = FALSE,
  est_sdr = FALSE,
  est_mov = c("none", "dist_random", "gravity_fixed"),
  est_qfs = FALSE,
  silent = FALSE
)

check_parameters(p = list(), map, MARSdata, silent = FALSE)

Arguments

MARSdata: S4 data object
start: An optional list of parameters. Named list of parameters with the associated dimensions and transformations below. Overrides default values created by make_parameters().
map: List of mapped parameters. Used by check_parameters() only to count parameters.
est_mov: Character describing structure of stock movement parameters. See details below.
silent: Logical, whether make_map() reports messages to the console
...: Various arguments for make_map() (could be important!)
p: List of parameters, e.g., returned by make_parameters()
est_M: Logical, estimate natural mortality?
est_h: Logical, estimate steepness?
est_mat: Logical, estimate maturity?
est_sdr: Logical, estimate standard deviation of recruitment deviates?
est_qfs: Logical, estimate relative catchability of stocks by each fleet? Fix log_q_fs for the first stock if TRUE

Value

make_parameters() returns a list of parameters ("p") concatenated with the output of make_map().

make_map() returns a named list containing parameter mappings ("map") and a character vector of random effects ("random").

check_parameters() invisibly returns the parameter list if no problems are encountered.

Parameters

Generally parameter names will have up to three components, separated by underscores. For example, log_M_s represents the natural logarithm of natural mortality, and is a vector by stock s.

The first component describes the transformation from the estimated parameter space to the normal parameter space, frequently, log or logit. Prefix t indicates some other custom transformation that is described below.

Second is the parameter name, e.g., M for natural mortality, rdev for recruitment deviates, etc.

Third is the dimension of the parameter variable and the indexing for the vectors, matrices, and arrays, e.g., y for year, s for stock. See MARSdata. Here, an additional index p represents some other number of parameters that is described below.

t_R0_s: Vector by s. Unfished recruitment, i.e., intersection of unfished replacement line and average stock recruit function, is represented as: R0_s <- exp(t_R0_s) * MARSdata@Dmodel@scale_s. By default, t_R0_s = 3
t_h_s: Vector by s. Steepness of the stock-recruit function. Logit space for Beverton-Holt and log space for Ricker functions. Default steepness value of 0.8
mat_ps: Matrix [2, s]. Maturity parameters (can be estimated or specified in data object). Logistic functional form. The parameter in the first row is the age of 50 percent maturity in logit space: a50_s <- plogis(mat_ps[1, ] * na). In the second row is the age of 95 percent maturity as a logarithmic offset: a95_s <- a50_s + exp(mat_ps[2, ]). Default a50_s <- 0.5 * na and a95_s <- a50_s + 1
log_M_s: Vector by s. Natural logarithm of natural mortality (can be estimated or specified in data object). Default parameter value for all stocks: M <- -log(0.05)/MARSdata@Dmodel@na
log_rdev_ys: Matrix [y, s]. Log recruitment deviations. By default, all start values are at zero.
log_sdr_s: Vector by s. log-Standard deviation of the log recruitment deviations. Default SD = 0.4
log_q_fs: Matrix [f, s]. The natural logarithm of q_fs, the relative fishing efficiency of f for stock s. Equal values imply equal catchability of all stocks. See equations in calc_F(). Default sets all values to zero.
log_Fdev_ymfr: Array [y, m, f, r]. Fishing mortality parameters. For each fleet, the log of F is estimated directly for the reference year, season, region. For other strata, F is an offset from this value: $$ F_{y,m,f,r} = \begin{cases} \exp(x^{\textrm{Fmult}}_f) \quad & y = y_{\textrm{ref}}, m = m_{\textrm{ref}}, r = r_{\textrm{ref}}\\ \exp(x^{\textrm{Fmult}}_f + x^{\textrm{Fdev}}_{y,m,r}) \quad & \textrm{otherwise} \end{cases} $$
sel_pf: Matrix [3, f]. Fishery selectivity parameters in logit or log space. See equations conv_selpar(), where sel_pf is the x matrix.
sel_pi: Matrix [3, i]. Index selectivity parameters in logit or log space. See equations conv_selpar(), where sel_pi is the x matrix.
mov_x_marrs: Array [m, a, r, r, s]. Base movement matrix. Set to -1000 to effectively exclude movements from region pairs. See equations in conv_mov()
mov_g_ymars: Array [y, m, a, r, s]. Attractivity term in gravity model for movement. If x and v are zero, this matrix specifies the distribution of total stock abundance into the various regions. See equations in conv_mov()
mov_v_ymas: Array [y, m, a, s]. Viscosity term in gravity model for movement. See equations in conv_mov()
log_sdg_rs: Array [r, s]. Marginal log standard deviation in the stock distribution (mov_g_ymars) among regions for stock s. Only used when est_mov = "dist_random". Default SD of 0.1.
t_corg_ps: Array [sum(1:(nr - 1)), s]. Lower triangle of the correlation matrix for mov_g_ymars, to be obtained with the Cholesky factorization. Only used when est_mov = dist_random. Default values of zero.
log_initF_mfr: Array [m, f, r]. Initial F corresponding to the equilibrium catch.
log_initrdev_as: Array [a, s]. Recruitment deviations for the initial abundance-at-age vector.

Start list

Users can provide R0_s and h_s in the start list. make_parameters() will make the appropriate transformation for the starting values of t_R0_s and t_h_s, respectively.

Movement setup for `make_map()`

If a single region model or est_mov = "none": no movement parameters are estimated.

If est_mov = "dist_random": fix all values for mov_x_marrs and mov_v_ymas. Fix mov_g_ymars for the first region for each year, season, age, and stock. mov_g_ymars are random effects.

If est_mov = "gravity_fixed": fix all values for mov_x_marrs. Fix mov_g_ymars for the first region for each year, season, age, and stock. Estimate all mov_v_ymas. Both mov_g_ymars and mov_v_ymas are fixed effects.

By default p$mov_x_marrs is zero. Set to -1000 for areas for which there is no abundance of a particular stock.