Divergence-based robust inference under proportional hazards model for one-shot device life-test

2020/04/28 by N. Balakrishnan, Elena Castilla, Balakrishnan, N. +4
Decision Sciences · Mathematics · #Advanced Statistical Methods and Models #Advanced Statistical Process Monitoring #Applications (stat.AP) #FOS: Computer and information sciences #Statistical Distribution Estimation and Applications

paper · pdf · doi:10.48550/arxiv.2004.13382

openalex publication_date 2020/04/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In this paper, we develop robust estimators and tests for one-shot device testing under proportional hazards assumption based on divergence measures. Through a detailed Monte Carlo simulation study and a numerical example, the developed inferential procedures are shown to be more robust than the classical procedures, based on maximum likelihood estimators.

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