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Often it can make sense to fit an additional model to get a grasp on the range of values that "beta" parameters can take. This function takes an existing BiodiversityDistribution object and creates PriorList object from them. The resulting object can be used to add for instance priors to a new model.

Usage

get_priors(mod, target_engine, ...)

# S4 method for ANY,character
get_priors(mod, target_engine, ...)

Arguments

mod

A fitted DistributionModel object. If instead a BiodiversityDistribution object is passed to this function, it simply returns the contained priors used for estimation (if any).

target_engine

A character for which the priors should be created.

...

Other parameters passed down.

Note

Not all engines support priors in similar ways. See the vignettes and help pages on that topic!

Examples

if (FALSE) {
 mod <- distribution(background) |>
    add_predictors(covariates) |>
    add_biodiversity_poipo(points) |>
    engine_inlabru() |>
    train()
 get_priors(mod, target_engine = "BART")
}