The goodness of a predictive distribution depends on the aim of the prediction. This presentation intends to shed light on properties of predictive distributions in use nowadays. We also propose a new predictive distribution that may be useful to obtain calibrated predictions for the probabilities of a future random variable of interest. This predictive distribution can be easily computed by a simple bootstrap procedure. In order to compare the different predictive distributions, some simulation studies are also presented.
Probabilistic prediction: aims and solutions
Giovanni Fonseca;Paolo Vidoni
2022-01-01
Abstract
The goodness of a predictive distribution depends on the aim of the prediction. This presentation intends to shed light on properties of predictive distributions in use nowadays. We also propose a new predictive distribution that may be useful to obtain calibrated predictions for the probabilities of a future random variable of interest. This predictive distribution can be easily computed by a simple bootstrap procedure. In order to compare the different predictive distributions, some simulation studies are also presented.File in questo prodotto:
Non ci sono file associati a questo prodotto.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.