Maximum observed likelihood prediction of future record values
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Grigoriy Volovskiy [1] ; Udo Kamps [1]
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[1] Rheinisch-Westfälische Technische Hochschule Aachen University
Rheinisch-Westfälische Technische Hochschule Aachen University
Städteregion Aachen, Alemania
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- Localización: Test: An Official Journal of the Spanish Society of Statistics and Operations Research, ISSN-e 1863-8260, ISSN 1133-0686, Vol. 29, Nº. 4, 2020, págs. 1072-1097
- Idioma: inglés
- Texto completo no disponible (Saber más ...)
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Resumen
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.
