Parameter estimates of general failure rate model: A Bayesian approach

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS

卷:351

Article

Nanda, Asok K.¹  Maiti, Sudhansu S.²  Kundu, Chanchal³  Kundu, Amarjit⁴ 

[1] Indian Inst Sci Educ & Res Kolkata, Dept Math & Stat, Mohanpur 741246, India

[2] Visva Bharati Univ, Dept Stat, Santini Ketan 731235, W Bengal, India

[3] Rajiv Gandhi Inst Petr Technol, Dept Math, Jais 229304, Amethi, India

[4] Raiganj Univ, Dept Math, Uttar Dinajpur, W Bengal, India

关键词: Farlie-Gumbell-Morgenstern family of distributions;    IFR and DFR classes;    Markov Chain Monte Carlo simulation;    Type-II censoring;   

DOI  :  10.1016/j.cam.2018.11.002

来源: Elsevier

【 摘 要 】

The failure rate function plays an important role in studying the lifetime distributions in reliability theory and life testing models. A study of the general failure rate model r(t) = a+bt(0-1). under squared error loss function, taking a and b independent exponential random variables, has been performed in the literature. In this article, we consider a and b not necessarily independent. The estimates of the parameters a and b under squared error loss, linex loss and entropy loss functions are obtained, and further examined using simulated and real data sets. (C) 2018 Elsevier B.V. All rights reserved.

【 授权许可】

Free