Prediction of record values by using quantile regression curves and distortion functions

Jorge Navarro ()
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Jorge Navarro: Universidad de Murcia

Metrika: International Journal for Theoretical and Applied Statistics, 2022, vol. 85, issue 6, No 2, 675-706

Abstract: Abstract The purpose of the paper is to provide a general method based on conditional quantile curves to predict record values from preceding records. The predictions are based on conditional median (or median regression) curves. Moreover, conditional quantiles curves are used to provide confidence bands for these predictions. The method is based on the recently introduced concept of multivariate distorted distributions that are used instead of copulas to represent the dependence structure. This concept allows us to compute the conditional quantile curves in a simple way. The theoretical findings are illustrated with a non-parametric model (standard uniform), two parametric models (exponential and Pareto), and a non-parametric procedure for the general case. A real data set and a simulated case study in reliability are analysed.

Keywords: Record values; Distorted distributions; Median regression; Confidence regions; Copula; 62F99; 62M20 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s00184-021-00847-w

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