In datalimited/datalimited: Stock Assessment Methods for Data-limited Fisheries

devtools::load_all("../")
x <- dplyr::filter(ram_ts, stocklong == "Albacore tuna Indian Ocean")
ct <- x$catch

out1 <- comsir(yr = x$year, ct = ct, k = 800, r = 0.6, x = 0.5, a = 0.8,
  start_r = resilience("medium"),
  mink = max(ct),
  maxk = max(ct) * 100, logk = TRUE, norm_k = FALSE, norm_r = FALSE,
  norm_a = FALSE, norm_x = FALSE, nsim = 1e5, cv = 0.4, logistic_model = TRUE,
  n_posterior = 5e3, normal_like = FALSE)

par(mfrow = c(2, 3));for(i in 1:6){hist(out1$posterior[,i], main = names(out1$posterior)[i])}

Try with normal priors:

out_normal <- comsir(yr = x$year, ct = ct, k = 800, r = 0.6, x = 0.5, a = 0.8,
  start_r = resilience("medium"),
  mink = max(ct),
  maxk = max(ct) * 100, logk = TRUE, norm_k = FALSE, norm_r = FALSE,
  norm_a = TRUE, norm_x = TRUE, nsim = 1e5, cv = 0.4, logistic_model = TRUE,
  n_posterior = 5e3, normal_like = FALSE)

par(mfrow = c(2, 3));for(i in 1:6){hist(out_normal$posterior[,i], main = names(out_normal$posterior)[i])}

out1 <- comsir(yr = x$year, ct = ct, k = 800, r = 0.6, x = 0.5, a = 0.8,
  start_r = resilience("medium"),
  mink = max(ct),
  maxk = max(ct) * 100, logk = TRUE, norm_k = FALSE, norm_r = TRUE,
  norm_a = TRUE, norm_x = TRUE, nsim = 1e5, cv = 0.8, logistic_model = TRUE,
  n_posterior = 5e3, normal_like = FALSE)

par(mfrow = c(2, 3));for(i in 1:6){hist(out1$posterior[,i], main = names(out1$posterior)[i])}