Bayesian Subset Selection for Inverse Gauss Regression Models
Yuanying Zhao, Dengke Xu, Liangqiong Jin, Qingqiong Jiang - · 2018
Inspired by the idea of Kuo and Mallick, Bayesian subset selection for inverse Gauss regression models is studied by Gibbs sampler and Metropolis-Hastings algorithm in this paper. Simulation study and the aerobic fitness data example are employed to demonstrate the proposed methodology.