MSAdata S4 object

S4 class that organizes the various data inputs for the MSA model. MSAdata simply inherits the slots from 6 component classes: Dmodel, Dstock, Dfishery, Dsurvey DCKMR, and Dtag, where the D- prefix denotes an object for data inputs (or model configuration).

Details

For convenience, most arrays and matrices have the associated dimensions in the variable name. For example, Cobs_ymfr represents observed catch with the dimension following the underscore, following this template:

`y`	Year
`m`	Season
`a`	Age
`r`	Region
`f`	Fishery
`i`	Index
`s`	Stock

Slots

Dmodel: Class Dmodel containing parameters for model structure (number of years, ages, etc.)
Dstock: Class Dstock containing stock parameters (growth, natural mortality, etc.)
Dfishery: Class Dfishery containing fishery data (catch, size and stock composition, etc.)
Dsurvey: Class Dsurvey containing survey data (indices of abundance)
DCKMR: Class DCKMR containing genetic close-kin data
Dtag: Class Dtag containing tagging data
Dlabel: Class Dlabel containing names for various dimensions. Used for plotting.
Misc: List for miscellaneous inputs as needed

Slots inherited from Dmodel

ny: Integer, number of years
nm: Integer, number of seasons
na: Integer, number of ages. The first age class is zero and the last age class (plus group is age na - 1).
nl: Integer, number of length bins. Set to zero if lengths are not modeled.
nr: Integer, number of spatial regions
ns: Integer, number of stocks
lbin: Vector of lower boundary of length bins. Length nl + 1
lmid: Vector of midpoint of length bins. Length nl
Fmax: Numeric, maximum allowable instantaneous fishing mortality rate (units of per season). Defaults to 3.
y_phi: Integer, the year from which to obtain values of natural mortality and fecundity for the unfished stock-recruit replacement line (phi). Relevant if natural mortality or fecundity are time-varying. Defaults to 1.
scale_s: Vector, length ns. Multiplicative scaling factor that informs relative stock size to aid parameter estimation. Larger values implies larger stocks. Default set to 1. See make_parameters().
nyinit: Integer, number of years of spool-up to calculate equilibrium unfished and starting conditions for the population model to account for seasonal and spatial dynamics. The numerical spool-up is not needed when both nm = 1 and nr = 1, i.e., nyinit = 1. Otherwise, set to 2 * na by default.
condition: Character, either to specify the model estimates fishing mortality as a parameter ("F", default) or equal to the catch ("catch").
nitF: Integer, number of iterations to solve Baranov catch equation from observed catch if condition = "catch". Defaults to 5.
y_Fmult_f: Integer vector by fleet, the year in which to directly estimate F. Choose a year/season/region combination when the catch is average relative to the time series. Only used if condition = "F".
m_Fmult_f: Integer vector by fleet, the season in which to directly estimate F. Choose a year/season/region combination when the catch is average relative to the time series. Only used if condition = "F".
r_Fmult_f: Integer vector by fleet, the region in which to directly estimate F. Choose a year/season/region combination when the catch is average relative to the time series. Only used if condition = "F".
pbc_rdev_ys: Numeric matrix, for the fraction of lognormal bias correction (-0.5 * sd_r^2) applied to the recruitment estimates in the model. Typically between 0-1, with default of 1.
pbc_initrdev_as: Numeric matrix, for the fraction of lognormal bias correction (-0.5 * sd_r^2) applied to the initial abundance vector in the model. Typically between 0-1, with default of 1.
prior: Character vector to be evaluated in the model to return the log prior for a parameter. See example in documentation for prior.
nyret: Integer, number of recent years of data to remove from the likelihood for retrospective analysis (positive numbers). Default is zero.

Slots inherited from Dstock

m_spawn: Integer, season of spawning. Defaults to 1. The progeny will enter the age structure in the same season.
m_advanceage: Integer, season in which to advance age classes (corresponding to calendar year) to the next age class. Defaults to 1.
len_ymas: Length-at-age. Only needed if Dmodel@nl > 0 to fit length composition (you may want to calculate the growth at the middle of the time step). calc_growth() may be a helpful function.
sdlen_ymas: Standard deviation in length-at-age
LAK_ymals: Length-at-age probability array. If empty, values will be calculated by check_data() with calc_LAK().
mat_yas: Proportion mature by age class. Ignored if maturity ogive is estimated, e.g., when fitting to close-kin genetic data.
swt_ymas: Stock weight-at-age (at beginning of time step). See calc_growth() example.
fec_yas: Fecundity, i.e., spawning output, of mature animals. Default uses stock weight at age.
M_yas: Natural mortality. Instantaneous units per year. Ignored if M is estimated.
SRR_s: Character vector of stock-recruit relationship by stock. See SRR argument in calc_recruitment() for options.
delta_s: Fraction of season that elapses when spawning occurs, e.g., midseason spawning occurs when delta_s = 0.5. Default is zero.
presence_rs: Logical matrix indicating presence/absence of stock s in region r. Used to constrain movement matrix. Default is TRUE for all stocks and regions.
natal_rs: The fraction of the mature stock s in region r that spawns at time of spawning. See example. Default is 1 for all stocks and regions.

Slots inherited from Dfishery

nf: Integer, number of fleets
Cobs_ymfr: Total fishery catch
Csd_ymfr: Lognormal standard deviation of the fishery catch. Only used if Dmodel@condition = "F". Default of 0.01.
fwt_ymafs: Fishery weight at age. Set to 1 when fleet catch is in units of abundance. Set to stock weight at age by default (values at beginning of time step).
CAAobs_ymafr: Fishery catch at age composition
CALobs_ymlfr: Fishery catch at length composition
fcomp_like: Character, likelihood for the fishery composition data. See type argument of like_comp() for options
CAAN_ymfr: Sample size of the catch at age vector by season if using the multinomial or Dirichlet-multinomial likelihoods
CALN_ymfr: Sample size of the catch at length vector by season if using the multinomial or Dirichlet-multinomial likelihoods
CAAtheta_f: Catch at age dispersion parameter if using the Dirichlet-multinomial likelihood. Default set to 1.
CALtheta_f: Catch at length dispersion parameter if using the Dirichlet-multinomial likelihood. Default set to 1.
sel_block_yf: Index of dummy fleets to model time blocks of selectivity
sel_f: Character vector of the functional form for selectivity. Choose between: "logistic_length", "dome_length", "logistic_age", "dome_age", "SB", "B"
Cinit_mfr: Equilibrium seasonal catch prior to the first year. One way to initialize the abundance at the start of the first year in the model. Default of zero.
SC_ymafrs: Stock composition data.
SC_aa: Boolean matrix that aggregates age classes for the stock composition data. See example.
SC_ff: Boolean matrix that aggregates fleets for the stock composition data. See example.
SC_like: Character, likelihood for the stock composition data. See type argument of like_comp() for options
SCN_ymafr: Sample size of the stock composition vector if using the multinomial or Dirichlet-multinomial likelihoods
SCtheta_f: Stock composition dispersion parameter if using the Dirichlet-multinomial likelihood. Default set to 1.
SCstdev_ymafrs: Stock composition standard deviation if using the lognormal likelihood. Default set to 0.1.

Slots inherited from Dsurvey

ni: Integer, number of indices of abundance. Zero is possible.
Iobs_ymi: Observed indices
Isd_ymi: Lognormal standard deviation of the observed indices
unit_i: Character vector, units of the index. Set to "B" to use stock weight at age (default) or "N" for abundance (numbers).
IAAobs_ymai: Array, survey age composition
IALobs_ymli: Array, survey length composition
icomp_like: Character, likelihood for the composition data. See like_comp() for options
IAAN_ymi: Array, sample size of the index age composition by season if using the multinomial or Dirichlet-multinomial likelihoods
IALN_ymi: Array, sample size of the index length composition by season if using the multinomial or Dirichlet-multinomial likelihoods
IAAtheta_i: Numeric vector, survey age composition dispersion parameter if using the Dirichlet-multinomial likelihood
IALtheta_i: Numeric vector, index length composition dispersion parameter if using the Dirichlet-multinomial likelihood
samp_irs: Boolean array that specifies the regions and stocks sampled by the index. samp[i, r, s] indicates whether index i operates in region r and catches stock s.
sel_i: Character vector, functional forms for selectivity. See "type" argument in conv_selpar() for options.
delta_i: Numeric vector, The elapsed fraction of time in the seasonal time step (between 0 - 1) when the index samples the population. Set to a negative number (-1) to sample over the duration of the timestep, i.e., (1 - exp(-Z))/Z.

Slots inherited from DCKMR

POP_s

A list by stock of data frames for parent-offspring pairs. Each row in the data frame corresponds to a "sampling unit" defined by the columns:

`a`	Capture year of parent
`t`	Age at capture of parent
`y`	Birth year of offspring
`n`	Number of pairwise comparisons
`m`	Number of POPs

HSP_s

A list by stock of data frames for half-sibling pairs. Each row in the data frame corresponds to a "sampling unit" defined by the columns:

`yi`	Birth year of older sibling
`yj`	Birth year of younger sibling
`n`	Number of pairwise comparisons
`m`	Number of HSPs

CKMR_like

Character, likelihood for the POP and HSP sampling units. See type argument in like_CKMR() for options.

Slots inherited from Dtag

tag_ymarrs: Array. Number of tags that move between regions. Informs movement matrices of stocks between time steps.
tag_ymars: Array. Number of tags distributed among regions. Informs stock distribution (within time step).
tag_yy: Boolean matrix that aggregates years for the tag data. Only used for the tag movement array tag_ymarrs.
tag_aa: Boolean matrix that aggregates ages for the tag data.
tag_like: Character. Likelihood for the tagging data, either the vector of proportions by region of origin for tag_ymarrs, or by region of stock distribution for tag_ymars. See type argument of like_comp() for options
tagN_ymars: Array. Sample size of the tag movement vectors if using the multinomial or Dirichlet-multinomial likelihoods.
tagN_ymas: Array. Sample size of the tag distribution vectors if using the multinomial or Dirichlet-multinomial likelihoods.
tagtheta_s: Array. Tag dispersion parameter (by stock) if using the Dirichlet-multinomial likelihoods. Default set to 1.
tagstdev_s: Array. Tag standard deviation (by stock) if using the lognormal likelihood. Default set to 0.1.

Slots inherited from Dlabel

year: Vector of years. Length Dmodel@ny
season: Vector of season names. Length Dmodel@nm
age: Vector of ages. Length Dmodel@na
region: Vector of region names. Length Dmodel@nr
stock: Vector of stock names. Length Dmodel@ns
fleet: Vector of fleet names. Length Dfishery@nf
index: Vector of index of abundance names. Length Dsurvey@ni

Examples

# Set natal_rs matrix so that the spawning output of stock 1 is
# calculated from mature animals present in regions 1, 2.
# Similarly for stock 2, spawning output from areas 2 and 3.
nr <- 4
ns <- 2
natal_rs <- matrix(0, nr, ns)
natal_rs[1:2, 1] <- natal_rs[2:3, 2] <- 1

# Aggregate stock composition for ages 1-4 and 5-10 across all fleets
na <- 10
na_SC <- 2
SC_aa <- matrix(0, na_SC, na) # Assumes dim(SC_ymafrs)[3] = na_SC
SC_aa[1, 1:4] <- SC_aa[2, 5:10] <- 1

nf <- 3
nf_SC <- 1
SC_ff <- matrix(1, nf_SC, nf) # Assumes dim(SC_ymafrs)[4] <- nf_SC