Forecasts based on DRM.

Considering a new dataset (across the same patches), computes forecasts based on the DRM passed as drm.

Usage

predict_drm(drm, new_data, past_data, f_test, seed = 1, cores = 1)

Arguments

drm

A list object containing the output from the fit_drm function.

new_data

a data.frame with the dataset at which we wish to obtain predictions.

past_data

a data.frame with the dataset last year used in model fitting. Only needed when f_test is not missing or when estimating survival.

f_test

a matrix informing the instantaneous fishing mortality rates at each age (columns) and timepoint (rows).

seed

a seed used for the forecasts. Forecasts are obtained through Monte Carlo samples from the posterior predictive distribution. Therefore, a seed is needed to ensure the results' reproducibility.

cores

number of threads used for the forecast. If four chains were used in the drm, then four (or less) threads are recommended.

Value

an object of class "CmdStanGQ" containing samples for the posterior predictive distribution for forecasting.

Details

The current version of the code assumes the data where forecasts are needed is ordered by "patch" and "site" and, in addition, its patches MUST be the same as the ones used to obtain the parameters' estimates from the the drm object.

Author

lcgodoy