Maximum observed likelihood prediction of future record values

Grigoriy Volovskiy () and Udo Kamps ()
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Grigoriy Volovskiy: RWTH Aachen University
Udo Kamps: RWTH Aachen University

TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, 2020, vol. 29, issue 4, No 14, 1072-1097

Abstract: Abstract Point prediction of future upper record values is considered. For an underlying absolutely continuous distribution with strictly increasing cumulative distribution function, the general form of the predictor obtained by maximizing the observed predictive likelihood function is established. The results are illustrated for the exponential, extreme-value and power-function distributions, and the performance of the obtained predictors is compared to that of maximum likelihood predictors on the basis of the mean squared error and the Pitman’s measure of closeness criteria. For exponential and extreme-value distributions, it is shown that under slight restrictions, the maximum observed likelihood predictor outperforms the maximum likelihood predictor in terms of both performance criteria.

Keywords: Maximum likelihood prediction; Maximum observed likelihood prediction; Upper record values; Exponential distribution; Extreme-value distribution; Power-function distribution; 62F99; 62M20 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s11749-020-00701-7

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