A semiparametric Bayesian approach to simplex regression model with heterogeneous dispersion

作者：Duan, Xing-De^*; Zhao, Yuan-Ying; Tang, An-Min

来源：Communications in Statistics - Simulation and Computation, 2019, 48(8): 2487-2500.

DOI：10.1080/03610918.2018.1458129

• Bayesian case-deletion diagnostics
• B-spline
• Continuous proportions
• Model comparison
• Simplex distribution
• Varying dispersion

Simplex regression model is often employed to analyze continuous proportion data in many studies. In this paper, we extend the assumption of a constant dispersion parameter (homogeneity) to varying dispersion parameter (heterogeneity) in Simplex regression model, and present the B-spline to approximate the smoothing unknown function within the Bayesian framework. A hybrid algorithm combining the block Gibbs sampler and the Metropolis-Hastings algorithm is presented for sampling observations from the posterior distribution. The procedures for computing model comparison criteria such as conditional predictive ordinate statistic, deviance information criterion, and averaged mean squared error are presented. Also, we develop a computationally feasible Bayesian case-deletion influence measure based on the Kullback-Leibler divergence. Several simulation studies and a real example are employed to illustrate the proposed methodologies.

• 出版日期2019-9-14
• 单位贵阳学院; 楚雄师范学院; 云南大学