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A robust extension of the bivariate Birnbaum–Saunders distribution and associated inference

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  • Vilca, Filidor
  • Balakrishnan, N.
  • Zeller, Camila Borelli

Abstract

We propose here a robust extension of the bivariate Birnbaum–Saunders (BS) distribution derived recently by Kundu et al. (2010). This extension is based on scale mixtures of normal (SMN) distributions that are used for modeling symmetric data. This type of bivariate Birnbaum–Saunders distribution based on SMN models is an absolutely continuous distribution whose marginals are of univariate Birnbaum–Saunders type. We then develop the EM-algorithm for the maximum likelihood (ML) estimation of the model parameters, and illustrate the obtained results with a real data and display the robustness feature of the estimation procedure developed here.

Suggested Citation

  • Vilca, Filidor & Balakrishnan, N. & Zeller, Camila Borelli, 2014. "A robust extension of the bivariate Birnbaum–Saunders distribution and associated inference," Journal of Multivariate Analysis, Elsevier, vol. 124(C), pages 418-435.
    • Handle: RePEc:eee:jmvana:v:124:y:2014:i:c:p:418-435
    DOI: 10.1016/j.jmva.2013.11.005
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    Cited by:

    1. Vilca, Filidor & Romeiro, Renata G. & Balakrishnan, N., 2016. "A bivariate Birnbaum–Saunders regression model," Computational Statistics & Data Analysis, Elsevier, vol. 97(C), pages 169-183.
    2. Min Wang & Xiaoqian Sun & Chanseok Park, 2016. "Bayesian analysis of Birnbaum–Saunders distribution via the generalized ratio-of-uniforms method," Computational Statistics, Springer, vol. 31(1), pages 207-225, March.
    3. Carolina Marchant & Víctor Leiva & Francisco José A. Cysneiros & Juan F. Vivanco, 2016. "Diagnostics in multivariate generalized Birnbaum-Saunders regression models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(15), pages 2829-2849, November.
    4. Wraith, Darren & Forbes, Florence, 2015. "Location and scale mixtures of Gaussians with flexible tail behaviour: Properties, inference and application to multivariate clustering," Computational Statistics & Data Analysis, Elsevier, vol. 90(C), pages 61-73.

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