PREDICTION: ADVANCES AND NEW RESEARCH

Prediction is reviewed and the most recent advances in the area are presented.

An objective of this paper is to study the Bayesian multisample prediction and give a concise form for the predictive density function of the observable in sample j based on the informative sample(s).

Applications are shown to a general class of population distributions which specializes to a wide spectrum of life testing distribution models. The uncertainty about the true value of the parameter(s) is measured by a general class of prior density functions.