Article ID Journal Published Year Pages File Type
415266 Computational Statistics & Data Analysis 2016 11 Pages PDF
Abstract

A Bayesian stochastic search variable selection (BSSVS) method is presented for variable selection in quantile regression (QReg) for ordinal models. A Markov Chain Monte Carlo (MCMC) method is adopted to draw the unknown quantities from the full posteriors. Through simulations and analysis of an educational attainment dataset, the performance of the proposed approach is compared with some existing approaches, showing that the proposed approach performs quite good in comparison to some other methods.

Related Topics
Physical Sciences and Engineering Computer Science Computational Theory and Mathematics
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