fit_ensemble_model: Fits the ensemble model
In EcoEnsemble: A General Framework for Combining Ecosystem Models

fit_ensemble_model

R Documentation

Fits the ensemble model

Description

fit_ensemble_model runs an MCMC of the ensemble model. This process can take a long time depending on the size of the datasets.

Usage

fit_ensemble_model(
  observations,
  simulators,
  priors,
  full_sample = TRUE,
  control = list(adapt_delta = 0.95),
  drivers = FALSE,
  MMod,
  ...
)

Arguments

`observations`	A `list` of length 2 containing observations and a covariance matrix. The first element is a `data.frame` or `matrix` with each column giving observations of each output of interest and each row a time. Rows should be named with the times and columns should be named the variables. The second element is is a `d \times d` `matrix` where `d` is the number of columns of the observations data frame / matrix. This matrix is the covariance matrix of the observations.
`simulators`	A `list` with length equal to the number of simulators. For each simulator, there is a `list` of 2 objects containing the simulator output and covariance matrix. The first element is a `data.frame` or `matrix` with each column giving a simulator outputs of interest and each row a time. Rows should be named with the times and columns should be named the variables. The second element is a `n_k \times n_k` `matrix` where `n_k` is the number of columns of the simulators output data frame / matrix. This matrix is the covariance matrix of the simulator outputs.
`priors`	An `EnsemblePrior` object specifying the prior distributions for the ensemble.
`full_sample`	A `logical` that runs a full sampling of the posterior density of the ensemble model if `TRUE`. If `FALSE`, returns the point estimate which maximises the posterior density of the ensemble model.
`control`	If creating a full sample, this is a named `list` of paramaters 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.
`drivers`	A `logical` indicating whether drivers have been used in combination with simulators. Default value is FALSE.
`MMod`	Not currently implemented.
`...`	Additional arguments passed to the function `rstan::sampling` or `rstan::optimizing`.

Value

An EnsembleFit object.

References

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

Examples



fit <- fit_ensemble_model(observations = list(SSB_obs, Sigma_obs),
               simulators = list(list(SSB_ewe, Sigma_ewe, "EwE"),
                                 list(SSB_fs,  Sigma_fs, "FishSUMS"),
                                 list(SSB_lm,  Sigma_lm, "LeMans"),
                                 list(SSB_miz, Sigma_miz, "Mizer")),
               priors = EnsemblePrior(4,
               ind_st_params = IndSTPrior(parametrisation_form = "lkj",
               var_params= list(1,1), cor_params = 10, AR_params = c(2, 2))),
               full_sample = FALSE) #Only optimise in this case

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