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Erschienen in:
Basic Statistics Kapitel lesen Erstes Kapitel lesen

2023 | OriginalPaper | Buchkapitel

35. Inference for Coherent Systems with Weibull Components Under a Simple Step-Stress Model

verfasst von : Narayanaswamy Balakrishnan, Debanjan Mitra, Xiaojun Zhu

Erschienen in: Springer Handbook of Engineering Statistics

Verlag: Springer London

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Abstract

Coherent systems are widely studied in reliability experiments. Under the assumption that the components of a coherent system follow a two-parameter Weibull distribution, maximum likelihood inference for n-component coherent systems with known signatures under a simple step-stress model is discussed in this paper. The detailed steps of the stochastic expectation maximization algorithm under this setup are also developed to obtain estimates of the model parameters. Asymptotic confidence intervals for the model parameters are constructed using the observed Fisher information matrix and missing information principle. Parametric bootstrap approach is used also to construct confidence intervals for the parameters. A method based on best linear unbiased estimators is developed to provide initial values that are needed for numerical computation of maximum likelihood estimates. The performance of the methods developed is assessed through an extensive Monte Carlo simulation study. Finally, two numerical examples are presented for illustrative purpose.

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Vorheriges Kapitel Deterministic and Stochastic DCA for DC Programming
Nächstes Kapitel Bivariate Distributions with Singular Components
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Metadaten
Titel
Inference for Coherent Systems with Weibull Components Under a Simple Step-Stress Model
verfasst von
Narayanaswamy Balakrishnan
Debanjan Mitra
Xiaojun Zhu
Copyright-Jahr
2023
Verlag
Springer London
Buch
Springer Handbook of Engineering Statistics

Print ISBN: 978-1-4471-7502-5

Electronic ISBN: 978-1-4471-7503-2

Copyright-Jahr: 2023

DOI
https://doi.org/10.1007/978-1-4471-7503-2_35

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