Dimension reduction based on conditional multiple index density function

作者：Zhang, Jun; He, Baohua^*; Lu, Tao; Wen, Songqiao

来源：Brazilian Journal of Probability and Statistics (Brazilian Stat. Assoc.), 2018, 32(4): 851-872.

DOI：10.1214/17-BJPS370

• Central subspace
• conditional density function
• dimensional reduction
• kernel function

In this paper, a dimension reduction method is proposed by using the first derivative of the conditional density function of response given predictors. To estimate the central subspace, we propose a direct methodology by taking expectation of the product of predictor and kernel function about response, which helps to capture the directions in the conditional density function. The consistency and asymptotic normality of the proposed estimation methodology are investigated. Furthermore, we conduct some simulations to evaluate the performance of our proposed method and compare with existing methods, and a real data set is analyzed for illustration.

• 出版日期2018-11
• 单位北京师范大学; 北京师范大学-香港浸会大学联合国际学院; 北京理工大学; 深圳大学