library(SimSurvey)
## Simulate cod-like population
## See "imitate_cod_data.R" file for details on parameter choices
set.seed(438)
pop <- sim_abundance(ages = 1:20,
years = 1:20,
R = sim_R(mean = 30000000,
log_sd = 0.5,
random_walk = TRUE),
Z = sim_Z(mean = 0.5,
log_sd = 0.2,
phi_age = 0.9,
phi_year = 0.5),
growth = sim_vonB(Linf = 120, L0 = 5, K = 0.1,
length_group = 3,
digits = 0)) %>%
sim_distribution(grid = sim_grid(x_range = c(-140, 140),
y_range = c(-140, 140),
res = c(3.5, 3.5),
shelf_depth = 200,
shelf_width = 100,
depth_range = c(0, 1000),
n_div = 1,
strat_breaks = seq(0, 1000, by = 20),
strat_splits = 2),
ays_covar = sim_ays_covar(sd = 2.8,
range = 300,
phi_age = 0.5,
phi_year = 0.9,
group_ages = 5:20),
depth_par = sim_parabola(mu = 200,
sigma = 70))
error <- pop %>%
sim_survey(n_sims = 10, age_sampling = "random") %>%
run_strat() %>%
strat_error()
rm(error)
## Test a series of surveys
## Simulate surveys and compare stratified estimates to the true index
setMKLthreads(1) # turn off MKL hyperthreading
surveys <- expand_surveys(set_den = c(2) / 1000,
lengths_cap = c(100),
ages_cap = c(3, 4))
sim <- test_surveys(pop,
surveys = surveys,
n_sims = 10,
n_loops = 100,
cores = 6,
q = sim_logistic(k = 2, x0 = 3),
age_sampling = "random") # export_dir = "tests/exports")
# sim <- resume_test(dir = "tests/exports")
setMKLthreads() # turn hyperthreading on again
plot_age_strat_fan(sim, surveys = 1:8, select_by = "age",
ages = sim$ages, years = sim$years)
sim$age_strat_error_stats
## Appears to be poorer performance with random vs length-stratified age sampling strategies
## Check consequences of narrow strata since it potentially contributes
## to the downward bias observed under the low set density scenario
library(raster)
grid <- sim_grid(x_range = c(-140, 140),
y_range = c(-140, 140),
res = c(3.5, 3.5),
shelf_depth = 250,
shelf_width = 0,
depth_range = c(0, 500),
n_div = 1,
strat_breaks = seq(0, 500, by = 25),
strat_splits = 2,
method = "linear")
plot(rasterToPolygons(grid$strat, dissolve = TRUE))
plot(grid)
set.seed(438)
pop <- sim_abundance(ages = 1:20,
years = 1:20,
R = sim_R(mean = 30000000,
log_sd = 0.5,
random_walk = TRUE),
Z = sim_Z(mean = 0.5,
log_sd = 0.2,
phi_age = 0.9,
phi_year = 0.5),
growth = sim_vonB(Linf = 120, L0 = 5, K = 0.1,
length_group = 3,
digits = 0)) %>%
sim_distribution(grid = grid,
ays_covar = sim_ays_covar(sd = 2.8,
range = 300,
phi_age = 0.5,
phi_year = 0.9,
group_ages = 5:20),
depth_par = sim_parabola(mu = 200,
sigma = 70))
error <- pop %>%
sim_survey(n_sims = 10, age_sampling = "random") %>%
run_strat() %>%
strat_error()
plot_samp_dist(error, which_year = 4)
rm(error)
## Test a series of surveys
## Simulate surveys and compare stratified estimates to the true index
setMKLthreads(1) # turn off MKL hyperthreading
surveys <- expand_surveys(set_den = c(0.0005),
lengths_cap = c(100),
ages_cap = c(10))
sim <- test_surveys(pop,
surveys = surveys,
n_sims = 10,
n_loops = 100,
cores = 6,
q = sim_logistic(k = 2, x0 = 3)) # export_dir = "tests/exports")
# sim <- resume_test(dir = "tests/exports")
setMKLthreads() # turn hyperthreading on again
plot_total_strat_fan(sim)
plot_distribution_slider(sim, ages = 1:20, years = 6)
plot_samp_dist(sim, which_year = 6, which_sim = 5)
mean(sim$total_strat_error$error)
hist(sim$total_strat_error[year == 6]$error, breaks = 100, xlab = "error", main = "")
abline(v = 0, col = "red")
abline(v = mean(sim$total_strat_error$error), col = "blue")
abline(v = median(sim$total_strat_error$error), col = "green")
## Note that the percentiles in the fan plot make it look slightly biased...but the mean would look better
## because it lands in a higher place on a skewed distribution
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