A function that develops a multiple fleet operating model (MOM) and either models a unisex or 2-sex stock from arrays of abundance, fishing mortality, and biological parameters. The user still needs to parameterize most of the observation and implementation portions of the operating model.
Assess2MOM(
Name = "MOM created by Assess2MOM",
proyears = 50,
interval = 2,
CurrentYr = as.numeric(format(Sys.Date(), "%Y")),
h = 0.999,
Obs = MSEtool::Imprecise_Unbiased,
Imp = MSEtool::Perfect_Imp,
naa,
faa,
waa,
Mataa,
Maa,
laa,
fecaa,
nyr_par_mu = 3,
LowerTri = 1,
recind = 0,
plusgroup = TRUE,
altinit = 0,
fixq1 = TRUE,
report = FALSE,
silent = FALSE,
...
)An object of class MOM.
Character string. The name of the multi-OM.
Positive integer. The number of projection years for MSE.
Positive integer. The interval at which management procedures will update the management advice in multiMSE, e.g., 1 = annual updates.
Positive integer. The current year (e.g., final year of fitting to data)
The steepness of the stock-recruitment curve. Either a single numeric or a length nsim vector.
Either a single observation model to be used for all sexes and populations (class Obs), or a list where
Obs[[f]] is the Obs object for fleet f (identical between sexes).
Either a single implementation model to be used for all sexes and populations (class Imp), or a list where
Imp[[f]] is the Obs object for fleet f (identical between sexes).
Numbers-at-age by sex [first age is age zero]. Four-dimensional numeric array [sim, ages, year, p]. [p] indexes the population, where
[p = 1] for females and [p = 2] for males.
Fishing mortality rate-at-age by sex and fleet [first age is age zero]. Five-dimensional numeric array [sim, ages, year, p, f] where [f] indexes fishery fleet.
Weight-at-age [first age is age zero]. Four-dimensional numeric array [sim, ages, year, p].
Maturity (spawning fraction)-at-age [first age is age zero]. Four-dimensional numeric array [sim, ages, year, p].
Natural mortality rate-at-age [first age is age zero]. Four-dimensional numeric array [sim, ages, year, p].
Length-at-age [first age is age zero]. Four-dimensional numeric array [sim, ages, year, p].
Fecundity at age [first age is age zero]. If missing, default fecundity is the product of maturity and weight at age.
Positive integer. The number of recent years that natural mortality, age vulnerability, weight, length and maturity parameters are averaged over for defining future projection conditions.
Integer. The number of recent years for which model estimates of recruitment are ignored (not reliably estimated by the assessment)
Positive integer. The first age class that fish 'recruit to the fishery'. The default is 0 - ie the first position in the age dimension of naa is age zero
Logical. Does the assessment assume that the oldest age class is a plusgroup?
Integer. Various assumptions for how to set up the initial numbers. 0: standard, 1: no plus group, 2: temporary fix for MSEtool plus group initialization
Logical. Should q be fixed (ie assume the F-at-age array faa is accurate?
Logical, if TRUE, a diagnostic will be reported showing the matching of the OM reconstructed numbers at age vs the assessment.
Whether to silence messages to the console.
Additional arguments (for all, either a numeric or a length nsim vector):
SRrel Stock-recruit relationship. (1 for Beverton-Holt (default), 2 for Ricker)
R0 unfished recruitment
phi0 unfished spawners per recruit associated with R0 and h. With time-varying parameters, openMSE uses the mean phi0
in the first ageM (age of 50 percent maturity) years for the stock-recruit relationship. Assess2OM will re-calculate R0 and h
in the operating model such that the stock-recruit alpha and beta parameters match values implied in the input.
Perr recruitment standard deviation (lognormal distribution) for sampling future recruitment
AC autocorrelation in future recruitment deviates.
Q. Huynh
Use a seed for the random number generator to sample future recruitment.
SS2MOM multiMSE Assess2OM