Progressive Type-II Censored Samples for Bivariate Weibull Distribution with Economic and Medical Applications

24-03-2022

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Authors: El-Sayed A. El-Sherpieny; Hiba Z. Muhammed; Ehab M. Almetwally
Published in: Annals of Data Science | Issue 1/2024

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Abstract

The Bivariate Weibull distribution, particularly the Farlie–Gumbel–Morgenstern (FGMBW) variant, is extensively used in economics and finance for risk management and in medical fields for studying dependencies between variables. This article introduces progressive Type-II censoring schemes for estimating the parameters of the FGMBW distribution using the maximum likelihood method. The study compares different censoring schemes through simulation studies and real-world data applications, highlighting the efficiency and accuracy of the proposed methods. The authors also provide guidelines for selecting the best censoring scheme, making this research highly relevant for practitioners and researchers in the fields of statistics, data science, and applied mathematics.

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Title: Progressive Type-II Censored Samples for Bivariate Weibull Distribution with Economic and Medical Applications
Authors: El-Sayed A. El-Sherpieny
Hiba Z. Muhammed
Ehab M. Almetwally
Publication date: 24-03-2022
Publisher: Springer Berlin Heidelberg
Published in: Annals of Data Science / Issue 1/2024
Print ISSN: 2198-5804
Electronic ISSN: 2198-5812
DOI: https://doi.org/10.1007/s40745-022-00375-y

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Progressive Type-II Censored Samples for Bivariate Weibull Distribution with Economic and Medical Applications

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