On a progressively censored competing risks data from Gompertz distribution. Issue 4 (3rd April 2023)

• Record Type: Journal Article
• Authors: Lodhi, Chandrakant; Tripathi, Yogesh Mani; Bhattacharya, Ritwik
• Is Part Of: Communications in statistics. Volume 52:Issue 4(2023)
• Page Start: 1278
• Page End: 1299
• Publication Date: 2023-04-03
• Subjects: Competing risks -- Gompertz distribution -- Maximum likelihood -- Missing information principle -- Multi-objective optimization -- Progressive Type-II censoring; 62F09 -- 62G34; Mathematical statistics -- Periodicals; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5
• DOI: 10.1080/03610918.2021.1879141
• Languages: English
• ISSNs: 0361-0918

Abstract

Abstract: We study a competing risks model using Gompertz distribution under progressive Type-II censoring when probability distributions of failure causes are identically distributed with common scale and different shape parameters. Maximum likelihood estimates (MLEs) of these parameters are obtained and their uniqueness and existence behavior are also discussed. The asymptotic intervals are derived from the observed Fisher information matrix. We compare the performance of all the estimators numerically using simulations. Analysis of a real data set is presented as well. We further determine optimal censoring scheme using expected Fisher information matrix. The design parameters are selected based on suitable measures like cost-based and variance-based criteria functions. Finally, we discuss single and multi-objective optimization approaches to find optimal censoring schemes.