general_surplus_production_model_sigma: general_surplus_production_model_sigma

In Craig44/stockassessmenthelper: Package to help plot stock assessment models and functionality

general_surplus_production_model_sigma

Description

that can be used as an operating model Different from the above uses a standard deviation for process error instead of CV and also allow for fishing to be input as both catch and exploitation.

Usage

general_surplus_production_model_sigma(
  seed = 123,
  n_t,
  B1,
  m,
  r,
  k,
  catches = NULL,
  exploitation = NULL,
  obs_std,
  catchability,
  observation_likelihood = 1,
  process_error = NULL,
  process_std = NULL,
  n_obs_series = 1
)

Arguments

seed	seed for random number generator
n_t	<integer> number of time-steps to run the model
B1	<real> starting exploited biomass
m	<real> shape parameter for the surplus production curve (m = 2 = schafer)
r	<real> intrinsic growth parameter.
k	<real> carrying capacity parameter.
catches	<vector> observed catches, defines number of years, so if you have a period of no catches set values of 0, number of years = length(catches+ 1)
exploitation	<vector> observed catches, defines number of years, so if you have a period of no catches set values of 0, number of years = length(catches+ 1
obs_std	<real> Standard deviation which is used to generate simulated observations.
catchability	<vector> a scalar to generate the relative index observation
observation_likelihood	<int> likelihood type, 1 = lognormal, 2 = normal, 3 = ...
process_error	(optional) time specific time deviations (epsilon_t,p) for each time step
process_std	(optional) standard deviation for process deviations corrections
n_obs_series	number relative indicies

Value

Returns a list of model quantities and observations

Craig44/stockassessmenthelper documentation built on April 14, 2023, 10:57 a.m.