Date of Award
2026-05-01
Degree Name
Master of Science
Department
Mathematical Sciences
Advisor(s)
Ritwik Bhattacharya
Abstract
Any life-testing experiments with censoring generate ordered failure data, which are used to estimate model parameters of the underlying lifetime distribution. However, predicting unobserved failure times is an important goal post inference. Balakrishnan and Bhattacharya [2021] showed that joint best linear unbiased predictors (BLUPs) are more efficient than their marginal counterparts. In this thesis, we introduce a compound optimal design to compute joint BLUPs based on a suitably chosen subset of the observed data. It is shown that the linear predictors of the parameters from any location-scale distribution, based on a few optimally chosen ranks, obtained from the compound optimal design criterion, are indeed the joint BLUPs. A real-world dataset is analyzed to illustrate the proposed strategy.
Language
en
Provenance
Received from ProQuest
Copyright Date
2026-05
File Size
55 p.
File Format
application/pdf
Rights Holder
Foster Nkansah
Recommended Citation
Nkansah, Foster, "Best Linear Unbiased Prediction Based On Optimally Selected Order Statistics Using Compound Design" (2026). Open Access Theses & Dissertations. 4748.
https://scholarworks.utep.edu/open_etd/4748