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Annals of Data Science
Published in:

15-06-2023

On Progressively Censored Generalized X-Exponential Distribution: (Non) Bayesian Estimation with an Application to Bladder Cancer Data

Authors: Kousik Maiti, Suchandan Kayal, Aditi Kar Gangopadhyay

Published in: Annals of Data Science | Issue 5/2024

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Abstract

This article addresses estimation of the parameters and reliability characteristics of a generalized X-Exponential distribution based on the progressive type-II censored sample. The maximum likelihood estimates (MLEs) are obtained. The uniqueness and existence of the MLEs are studied. The Bayes estimates are obtained under squared error and entropy loss functions. For computation of the Bayes estimates, Markov Chain Monte Carlo method is used. Bootstrap-t and bootstrap-p methods are used to compute the interval estimates. Further, a simulation study is performed to compare the performance of the proposed estimates. Finally, a real-life dataset is considered and analysed for illustrative purposes.
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Appendix
Available only for authorised users
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Metadata
Title
On Progressively Censored Generalized X-Exponential Distribution: (Non) Bayesian Estimation with an Application to Bladder Cancer Data
Authors
Kousik Maiti
Suchandan Kayal
Aditi Kar Gangopadhyay
Publication date
15-06-2023
Publisher
Springer Berlin Heidelberg
Published in
Annals of Data Science / Issue 5/2024
Print ISSN: 2198-5804
Electronic ISSN: 2198-5812
DOI
https://doi.org/10.1007/s40745-023-00477-1

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