Type I-Type II Mixture Censoring Scheme for Lifetime Data Analysis

Fuente: arXiv
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Autores principales: Anakha, K. K., Chacko, V. M.
Formato: Preprint
Publicado: 2023
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author Anakha, K. K.
Chacko, V. M.
author_facet Anakha, K. K.
Chacko, V. M.
contents The Type-I and Type-II censoring schemes are the most prominent and commonly used censoring schemes in practice. In this work, a mixture of Type-I and Type- II censoring schemes, named the Type I-Type II mixture censoring scheme, has been introduced. Different censoring schemes have been discussed, along with their benefits and drawbacks. For the proposed censoring scheme, we analyze the data under the assumption that failure times of experimental units follow the Weibull distribution. The computational formulas for the expected number of failures and the expected failure time are provided. Maximum likelihood estimation and Bayesian estimation are used to estimate the model parameters. On the basis of thorough Monte Carlo simulations, the investigated inferential approaches are evaluated. Finally, a numerical example is provided to demonstrate the method of inference discussed here.
format Preprint
id arxiv_https___arxiv_org_abs_2308_11660
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Type I-Type II Mixture Censoring Scheme for Lifetime Data Analysis
Anakha, K. K.
Chacko, V. M.
Methodology
Statistics Theory
The Type-I and Type-II censoring schemes are the most prominent and commonly used censoring schemes in practice. In this work, a mixture of Type-I and Type- II censoring schemes, named the Type I-Type II mixture censoring scheme, has been introduced. Different censoring schemes have been discussed, along with their benefits and drawbacks. For the proposed censoring scheme, we analyze the data under the assumption that failure times of experimental units follow the Weibull distribution. The computational formulas for the expected number of failures and the expected failure time are provided. Maximum likelihood estimation and Bayesian estimation are used to estimate the model parameters. On the basis of thorough Monte Carlo simulations, the investigated inferential approaches are evaluated. Finally, a numerical example is provided to demonstrate the method of inference discussed here.
title Type I-Type II Mixture Censoring Scheme for Lifetime Data Analysis
topic Methodology
Statistics Theory
url https://arxiv.org/abs/2308.11660