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Inferential Survival Analysis for Inverted NH Distribution Under Adaptive Progressive Hybrid Censoring with Application of Transformer Insulation

  • 21-05-2022
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Abstract

The article explores the application of inferential survival analysis for the inverted Nadarajah-Haghighi (INH) distribution under adaptive progressive hybrid censoring (AT-I PHCS) with a focus on transformer insulation. It discusses the properties and motivations behind the Nadarajah-Haghighi distribution and its inverted version, highlighting their superiority in modeling data with specific characteristics. The paper introduces various censoring schemes, including type-I and type-II hybrid censoring, and progressive type-II censoring. It delves into the methodologies for estimating parameters, including maximum likelihood estimation (MLE) and maximum product spacing (MPS), and constructs confidence intervals using asymptotic and bootstrap methods. The article also covers Bayesian estimation using Markov Chain Monte Carlo (MCMC) techniques. The real-world application of these methods is demonstrated through an analysis of transformer insulation data, showcasing the effectiveness of AT-I PHCS in scenarios where time constraints are crucial.

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Title
Inferential Survival Analysis for Inverted NH Distribution Under Adaptive Progressive Hybrid Censoring with Application of Transformer Insulation
Authors
O. E. Abo-Kasem
Ehab M. Almetwally
Wael S. Abu El Azm
Publication date
21-05-2022
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/s40745-022-00409-5
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