LNLIKE.BEACHED: Calculate the log-likelihood of the beach whale data

In antarctic-humpback-2019-assessment/HumpbackSIR: Use Sample-Importance-Resampling to Estimate Southern Humpback Abundance

Calculate the log-likelihood of the beach whale data

Description

Calculate the log-likelihood of the beach whale data

Usage

LNLIKE.BEACHED(beached_data, Pred_N, start_yr, q_anthro, d_anthro,
  p_anthro, log = TRUE)

Arguments

beached_data	Data on whale strandingsas a data.frame containing year, estimate of absolute abundance, and standard deviation
Pred_N	Predicted absolute abundance in numbers from GENERALIZED_LOGISTIC.
start_yr	The first year of the projection (assumed to be the first year in the catch series).
q_anthro	is the proportion of the population that will be killed each year from anthropogenic mortality
d_anthro	is the detection probability of carcasses on the beach (including the probability of washing up on shore)
p_anthro	is the proportion of the range of the species covered by monitoring
log	Return the log of the likelihood (TRUE/FALSE)
add_CV	Additional CV to add to variance of lognormal distribution sampled from priors$add_CV.

Value

the negative log-likelihood

antarctic-humpback-2019-assessment/HumpbackSIR documentation built on Nov. 6, 2023, 6:07 p.m.