Reliability estimation in multicomponent stress-strength model for Topp-Leone distribution

Akgul F. G.

JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, vol.89, no.15, pp.2914-2929, 2019 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 89 Issue: 15
  • Publication Date: 2019
  • Doi Number: 10.1080/00949655.2019.1643348
  • Journal Name: JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.2914-2929
  • Keywords: Multicomponent stress-strength, Topp-Leone distribution, ML estimation, Bayesian estimation, Lindley's approximation, Gibbs sampling, Monte-Carlo simulation, UPPER RECORD VALUES, GREATER-THAN Y), INTERVAL ESTIMATION, BAYESIAN-ESTIMATION, SYSTEM, INFERENCE, MOMENTS, FAMILY
  • Karadeniz Technical University Affiliated: No

Abstract

In this paper, we consider the estimation reliability in multicomponent stress-strength (MSS) model when both the stress and strengths are drawn from Topp-Leone (TL) distribution. The maximum likelihood (ML) and Bayesian methods are used in the estimation procedure. Bayesian estimates are obtained by using Lindley's approximation and Gibbs sampling methods, since they cannot be obtained in explicit form in the context of TL. The asymptotic confidence intervals are constructed based on the ML estimators. The Bayesian credible intervals are also constructed using Gibbs sampling. The reliability estimates are compared via an extensive Monte-Carlo simulation study. Finally, a real data set is analysed for illustrative purposes.