BAYES AND ROBUST BAYES PREDICTION WITH AN APPLICATION TO AIR TEMPERATURE PREDICTION

摘要

Prediction of a future observation on the basis of currently observed data is demanded in many theoretical and applied problems. In this paper, we introduce prediction of a future observation from scale models under the general entropy prediction loss function and deal with Bayes and Posterior Regret Gamma Minimax prediction and obtain general form of the predictors. We study and discuss the air temperature prediction problem and utilize the results using an available well-known data set. A simulation study is also provided to illustrate the practical utility of the prediction procedure.