This article concerns the construction of prediction intervals for time series models. The estimative or plug-in solution is usually not entirely adequate, since the (conditional) coverage probability may differ substantially from the nominal value. Prediction intervals with improved...

This paper reviews some recent results on the construction of improved prediction limits for time series models and presents a simple solution based on a fully conditional approach. A prediction limit, expressed as a modification of the estimative one, is obtained so that its conditional and...

In this article we consider the problem of prediction for a general class of Gaussian models, which includes, among others, autoregressive moving average time-series models, linear Gaussian state space models and Gaussian Markov random fields. Using an idea presented in Sjöstedt-De Luna and...