Sparse Bayesian multinomial probit regression model with correlation prior for high-dimensional data classification

作者：Yang Aijun; Jiang Xuejun^*; Liu Pengfei; Lin Jinguan

来源：Statistics & Probability Letters, 2016, 119: 241-247.

DOI：10.1016/j.spl.2016.08.008

• Sparse Bayesian method
• Multinomial probit model
• Correlation prior
• High-dimensional data classification

Selecting a small number of relevant genes for cancer classification has received a great deal of attention in microarray data analysis. In this paper, a sparse Bayesian multinomial probit regression model with correlation prior is proposed. Based on simulated and real datasets, we demonstrate that the proposed method performs better than five other competing methods in terms of variable selection and classification.

• 出版日期2016-12
• 单位南方科技大学; 江苏师范大学; 东南大学; 南京审计大学; 江苏大学; 南京林业大学