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Erschienen in:
Comparison of OSS Reliability Assessment Methods by Using Wiener Data Preprocessing Based on Deep Learning Kapitel lesen Erstes Kapitel lesen

2024 | OriginalPaper | Buchkapitel

Analysis of Progressively Censored Repair Time of Airborne Communication Transceiver with Burr-Hatke Exponential Model

verfasst von : Kartik Waliya, Alka Chaudhary, Abhishek Tyagi

Erschienen in: Reliability Engineering for Industrial Processes

Verlag: Springer Nature Switzerland

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Abstract

In this chapter, the parameter estimation of a Burr-Hatke exponential model based on the progressive type-II censored sample is investigated. Various methods of estimation for complete data are generalized to the case under progressive censored samples. These approaches comprise maximum likelihood, least squares, maximum product spacings, and Bayesian estimation. Interval estimate and coverage probability for the parameter are derived by the use of maximum likelihood and Bayesian estimation techniques. Markov chain Monte Carlo algorithm has been employed to obtain the Bayes estimator of the parameter with gamma prior under squared error loss function. A vast comparative analysis of the four methods is made using a Monte Carlo empirical study. The empirical findings are used in the formulation of certain suggestions, and a real-world data example is shown to illustrate how the developed theory may be applied in practice.

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Vorheriges Kapitel Fault Removal Efficiency: A Key Driver in Software Reliability Growth Modeling
Nächstes Kapitel Bug Prediction Techniques: Analysis and Review
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Metadaten
Titel
Analysis of Progressively Censored Repair Time of Airborne Communication Transceiver with Burr-Hatke Exponential Model
verfasst von
Kartik Waliya
Alka Chaudhary
Abhishek Tyagi
Copyright-Jahr
2024
Buch
Reliability Engineering for Industrial Processes

Print ISBN: 978-3-031-55047-8

Electronic ISBN: 978-3-031-55048-5

Copyright-Jahr: 2024

DOI
https://doi.org/10.1007/978-3-031-55048-5_8

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