A Bayesian Inference Approach for Bivariate Weibull Distributions Derived from Roy and Morgenstern Methods

  • Ricardo Puziol de Oliveira State University of Maring
  • Marcos Vinicius de Oliveira Peres University of São Paulo
  • Milene Regina dos Santos University of São Paulo
  • Edson Zangiacomi Martinez University of São Paulo
  • Jorge Aberto Achcar University of São Paulo
Keywords: Bayesian analysis, bivariate lifetime model, Morgenstern family, stress-strength property

Abstract

Bivariate lifetime distributions are of great importance in studies related to interdependent components, especially in engineering applications. In this paper, we introduce two bivariate lifetime assuming three- parameter Weibull marginal distributions. Some characteristics of the proposed distributions as the joint survival function, hazard rate function, cross factorial moment and stress-strength parameter are also derived. The inferences for the parameters or even functions of the parameters of the models are obtained under a Bayesian approach. An extensive numerical application using simulated data is carried out to evaluate the accuracy of the obtained estimators to illustrate the usefulness of the proposed methodology. To illustrate the usefulness of the proposed model, we also include an example with real data from which it is possible to see that the proposed model leads to good fits to the data.

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Published
2021-07-12
How to Cite
Ricardo Puziol de Oliveira, Marcos Vinicius de Oliveira Peres, Milene Regina dos Santos, Edson Zangiacomi Martinez, & Jorge Aberto Achcar. (2021). A Bayesian Inference Approach for Bivariate Weibull Distributions Derived from Roy and Morgenstern Methods. Statistics, Optimization & Information Computing, 9(3), 529-554. https://doi.org/10.19139/soic-2310-5070-1240
Section
Research Articles