Coverage probability of prediction intervals for discrete random variables

Hsiuying Wang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

20 Scopus citations


Prediction interval is a widely used tool in industrial applications to predict the distribution of future observations. The exact minimum coverage probability and the average coverage probability of the conventional prediction interval for a discrete random variable have not been accurately derived in the literature. In this paper, procedures to compute the exact minimum confidence levels and the average confidence levels of the prediction intervals for a discrete random variable are proposed. These procedures are illustrated with examples and real data applications. Based on these procedures, modified prediction intervals with the minimum coverage probability or the average coverage probability close to the nominal level can be constructed.

Original languageEnglish
Pages (from-to)17-26
Number of pages10
JournalComputational Statistics and Data Analysis
Issue number1
StatePublished - 15 Sep 2008


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