This function plots the evolution of the tuning parameters for a 'dsc' object and returns basic performance metrics.
# S3 method for dsc_obj
summary(object, eval_period = NULL, ...)A list containing:
A list with the mean squared error (MSE) and squared errors (SE).
A list with the average continuous ranked probability score (ACRPS) and CRPS values.
A list with the average predictive log-likelihood (APLL) and predictive log-likelihood (PLL) values.
A list of ggplot objects for visualizing the tuning parameters and selected CFMs.
An object of type 'dsc'.
(Optional) A vector of indices to specify the evaluation period. Defaults to the entire period after burn-in.
Additional arguments to be consistent with the S3 print() function.
Gneiting, T., Raftery, A. E., Westveld, A. H., and Goldman, T. (2005): Calibrated Probabilistic Forecasting Using Ensemble Model Output Statistics and Minimum CRPS Estimation. Monthly Weather Review, 133: 1098–1118.
Jordan, A., Krueger, F., and Lerch, S. (2019): "Evaluating Probabilistic Forecasts with scoringRules." Journal of Statistical Software, 90(12): 1-37.
# \donttest{
# See example for tvc().
# }
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