prior_ensemble_model: Generate samples of parameters from prior distribution

In EcoEnsemble: A General Framework for Combining Ecosystem Models

Generate samples of parameters from prior distribution

Description

Methods to generates samples of the parameters from the prior distribution of the ensemble model.

Usage

prior_ensemble_model(
  priors,
  M = 1,
  MM = NULL,
  full_sample = TRUE,
  control = list(adapt_delta = 0.95),
  ...
)

Arguments

priors	An EnsemblePrior object specifying the prior distributions for the ensemble.
M	A numeric that represents the number of simulators. The default is 1.
MM	A numeric that represents the number of drivers. The default is NULL.
full_sample	A logical that runs a full sampling of the prior density of the ensemble model if TRUE. If FALSE, returns the point estimate which maximises the prior density of the ensemble model.
control	If creating a full sample, this is a named list of parameters to control Stan's sampling behaviour. See the documentation of the stan() function in the rstan package for details. The default value is list(adapt_delta = 0.95). If optimizing, this value is ignored.
...	Additional arguments passed to the function rstan::sampling or rstan::optimizing.

Value

A list containing two items named samples and point_estimate. If full_sample==TRUE, samples is a stanfit and point_estimate is a NULL object, else samples is a NULL and point_estimate is a list object. It is possible to generate a point estimate for the prior if the individual short-term discrepancy prior follows a hierarchical parameterisation.

References

Stan Development Team (2020). RStan: the R interface to Stan. R package version 2.21.2. https://mc-stan.org

See Also

EnsembleFit

Examples

priors <- EnsemblePrior(4)
prior_density <- prior_ensemble_model(priors, M = 4)

EcoEnsemble documentation built on April 4, 2025, 1:55 a.m.