D-optimal joint best linear unbiased prediction of order statistics

Narayanaswamy Balakrishnan () and Ritwik Bhattacharya ()
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Narayanaswamy Balakrishnan: McMaster University
Ritwik Bhattacharya: Tecnológico de Monterrey

Metrika: International Journal for Theoretical and Applied Statistics, 2022, vol. 85, issue 2, No 5, 253-267

Abstract: Abstract In life-testing experiments, it is often of interest to predict unobserved future failure times based on observed early failure times. A point best linear unbiased predictor (BLUP) has been developed in this context by Kaminsky and Nelson (J Am Stat Assoc 70:145–150, 1975). In this article, we develop joint BLUPs of two future failure times based on early failure times by minimizing the determinant of the variance–covariance matrix of the predictors. The advantage of applying joint prediction is demonstrated by using two real data sets. The non-existence of joint BLUPs in certain setups is also discussed.

Keywords: Best linear unbiased estimate (BLUE); Best linear unbiased predictor (BLUP); Location-scale family of distribution; Lagrangian method; Order statistics; Scale family of distributions; Type-II right censored samples; Variance–covariance matrix (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:metrik:v:85:y:2022:i:2:d:10.1007_s00184-021-00835-0

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DOI: 10.1007/s00184-021-00835-0

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