In this work we address the problem of the construction of prediction regions and distribution functions, with particular regard to the multidimensional setting. Firstly, we define a simple procedure for calculating the predictive distribution function which gives improved prediction limits. Secondly, with a multivariate generalization of a result presented in Ueki and Fueda(2007), we propose a method for correcting estimative prediction regions, to reduce their coverage error to the third-order accuracy. The improved prediction regions and the associated distribution functions are easy to calculate using a suitable bootstrap procedure. Examples of application are included, showing the good performance of the proposed method, even if we consider an approximated model for prediction purposes.
|Data di pubblicazione:||2012|
|Titolo:||A note about calibrated prediction regions and distributions|
|Rivista:||JOURNAL OF STATISTICAL PLANNING AND INFERENCE|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.1016/j.jspi.2012.03.010|
|Appare nelle tipologie:||2.1 Articolo su rivista |
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