This vignette introduces how to run MSE for a single stock without spatial structure:
library(wham)
library(whamMSE)
main.dir = here::here()
year_start <- 1 # starting year in the burn-in period
year_end <- 20 # end year in the burn-in period
MSE_years <- 3 # number of years in the feedback loop
# Note: no need to include MSE_years in simulation-estimation
info <- generate_basic_info(n_stocks = 1,
n_regions = 1,
n_indices = 1,
n_fleets = 1,
n_seasons = 1,
base.years = year_start:year_end,
n_feedback_years = MSE_years,
life_history = "medium",
n_ages = 12)
basic_info = info$basic_info # collect basic information
catch_info = info$catch_info # collect fleet catch information
index_info = info$index_info # collect survey information
F_info = info$F # collect fishing information
n_stocks <- as.integer(basic_info['n_stocks'])
n_regions <- as.integer(basic_info['n_regions'])
n_fleets <- as.integer(basic_info['n_fleets'])
n_indices <- as.integer(basic_info['n_indices'])
n_ages <- as.integer(basic_info['n_ages'])
# Selectivity Configuration
fleet_pars <- c(5,1)
index_pars <- c(2,1)
sel <- list(model=rep("logistic",n_fleets+n_indices),
initial_pars=c(rep(list(fleet_pars),n_fleets),rep(list(index_pars),n_indices)))
# M Configuration
M <- list(model="constant",initial_means=array(0.2, dim = c(n_stocks,n_regions,n_ages)))
sigma <- "rec+1"
re_cor <- "iid"
ini.opt <- "equilibrium"
sigma_vals <- array(0.5, dim = c(n_stocks, n_regions, n_ages)) # NAA sigma
NAA_re <- list(N1_model=rep(ini.opt,n_stocks),
sigma=rep(sigma,n_stocks),
cor=rep(re_cor,n_stocks),
recruit_model = 2, # rec random around the mean
sigma_vals = sigma_vals) # NAA_where must be specified in basic_info!
Here we use prepare_wham_input()
function to generate a
wham input using the basic information we set above:
input <- prepare_wham_input(basic_info = basic_info,
selectivity = sel,
M = M,
NAA_re = NAA_re,
catch_info = catch_info,
index_info = index_info,
F = F_info)
random = input$random # check what processes are random effects
input$random = NULL # so inner optimization won't change simulated RE
om <- fit_wham(input, do.fit = F, do.brps = T, MakeADFun.silent = TRUE)
# Note: do.fit must be FALSE (no modeling fitting yet)
om_with_data <- update_om_fn(om, seed = 123, random = random)
assess.interval <- 3 # Note: assessment interval is 3 years, given the feedback period is 3 years, there will be only 1 assessment
base.years <- year_start:year_end # Burn-in period
first.year <- head(base.years,1)
terminal.year <- tail(base.years,1)
assess.years <- seq(terminal.year, tail(om$years,1)-assess.interval,by = assess.interval)
mod = loop_through_fn(om = om_with_data,
em_info = info,
random = random,
M_em = M,
sel_em = sel,
NAA_re_em = NAA_re,
age_comp_em = "multinomial",
em.opt = list(separate.em = FALSE,
separate.em.type = 3,
do.move = FALSE,
est.move = FALSE),
assess_years = assess.years,
assess_interval = assess.interval,
base_years = base.years,
year.use = 20,
add.years = TRUE,
# add.years=TRUE: assessment will use 20 years of data from historical period + new years in the feedback period
seed = 123,
save.sdrep = TRUE,
save.last.em = TRUE,
do.retro = TRUE, # Perform retrospective analysis
do.osa = TRUE) # Perform OSA residual analysis