This is for use by developers.
Usage
model_recruitment(
data,
year_random = TRUE,
year_trend = TRUE,
adult_female_proportion = 0.65,
sex_ratio = 0.5,
demographic_stochasticity = TRUE,
priors = NULL
)
Arguments
- data
The data.frame.
- year_random
A flag indicating whether to include year random effect. If FALSE, year is fitted as a fixed effect.
- year_trend
A flag indicating whether to fit a year trend effect. Year trend cannot be fit if there is also a fixed year effect (as opposed to random effect).
- adult_female_proportion
A number between 0 and 1 of the expected proportion of adults that are female. If NULL, the proportion is estimated from the data (i.e.,
Cows ~ Binomial(adult_female_proportion, Cows + Bulls)
) and a prior of dbeta(65, 35) is used. This prior can be changed via thepriors
argument.- sex_ratio
A number between 0 and 1 of the proportion of females at birth.
- demographic_stochasticity
A flag indicating whether to include demographic_stochasticity in the recruitment model.
- priors
A named vector of the parameter prior distribution values. Any missing values are assigned their default values in
priors_survival()
andpriors_recruitment()
. If NULL, all parameters are assigned their default priors.