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27-04-2022

Competing Risk Analysis in Constant Stress Partially Accelerated Life Tests Under Censored Information

Authors: Intekhab Alam, Sadia Anwar, Lalit Kumar Sharma, Aquil Ahmed

Published in: Annals of Data Science | Issue 5/2023

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Abstract

This article presents a comprehensive study on competing risk analysis in constant stress partially accelerated life tests (CSPALT) under censored information. The focus is on the Fréchet distribution, a widely used model in extreme value theory, under Type-I and Type-II censoring schemes. The study introduces a novel framework for estimating parameters in CSPALT under competing risk plans, including the construction of likelihood functions, Fisher Information Matrix, and variance-covariance matrix. The authors conduct a simulation study to evaluate the performance of the estimators and highlight the practical applications of CSPALT in industrial settings. The article concludes by emphasizing the robustness and stability of the proposed test design, encouraging further research in different failure models and censoring plans.
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Metadata
Title
Competing Risk Analysis in Constant Stress Partially Accelerated Life Tests Under Censored Information
Authors
Intekhab Alam
Sadia Anwar
Lalit Kumar Sharma
Aquil Ahmed
Publication date
27-04-2022
Publisher
Springer Berlin Heidelberg
Published in
Annals of Data Science / Issue 5/2023
Print ISSN: 2198-5804
Electronic ISSN: 2198-5812
DOI
https://doi.org/10.1007/s40745-022-00401-z

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