get_pstar: Get pstar - Estimate Breakdown Point of Catch Counts

In pbs-assess/gfsynopsis: Data Synopsis Reports for PBS Groundfish

Get pstar - Estimate Breakdown Point of Catch Counts

Description

Fits a Generalized Additive Model (GAM) and calculates the breakdown point (pstar) of observed catch counts due to hook competition.

Usage

get_pstar(
  survey_dat,
  gam_formula,
  survey_type,
  prop_removed_min = NULL,
  h = 0.005,
  pstar_cache = NULL,
  save_out = TRUE
)

Arguments

survey_dat	A dataframe from prep_stitch_dat() or prep_iphc_stitch_dat().
gam_formula	A string or formula specifying the generalised additive used to estimate pstar. (See Watson et al. 2023). Suggestion for IPHC catch ~ -1 + s(prop_removed) + fyear + s(fstation, bs = "re") + offset(log_eff_skate) Suggestion for HBLL catch ~ -1 + s(prop_removed) + fyear + offset(log(hook_count)).
survey_type	A string specifying the survey type: "iphc", "hbll_outside", or "hbll_inside".
prop_removed_min	Optional. Minimum value of proportion of baits removed for generating predictions. If not provided, uses the minimum value found in survey_dat.
h	Step size for the central difference approximation (default = 0.005).
pstar_cache	Path to a folder for caching pstar objects.
save_out	Whether to save the pstar object to pstar_cache (default = TRUE). #' @references Watson, J., Edwards, A.M., and Auger-Méthe M. 2023. A statistical censoring approach accounts for hook competition in abundance indices from longline surveys. Can. J. Fish. Aquat. Sci. 80(3): 468-486. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1139/cjfas-2022-0159")}

Value

A list of objects containing

• gam_fit: The fitted GAM object.

• pred_df: A data frame with predicted values from gam_fit

• f1: A data frame containing the numerical approximation of the first derivative

• pstar_df: A data frame with the estimated pstar value.

• species: A character vector containing the species name.

pbs-assess/gfsynopsis documentation built on March 26, 2024, 7:30 p.m.