Dimension reduction with expectation of conditional difference  

作　　者：Wenhui Sheng Qingcong Yuan 

机构地区：[1]Department of Mathematical and Statistical Sciences,Marquette University,Milwaukee,WI,USA [2]Biostatistics and Programming,SanofiUS,Bridgewater,NJ,USA

出　　处：《Statistical Theory and Related Fields》2023年第3期188-201,共14页统计理论及其应用（英文）

摘　　要：In this article,we introduce a flexible model-free approach to sufficient dimension reduction analysis using the expectation of conditional difference measure.Without any strict conditions,such as linearity condition or constant covariance condition,the method estimates the central subspace exhaustively and efficiently under linear or nonlinear relationships between response and predictors.The method is especially meaningful when the response is categorical.We also studiedthe√n-consistency and asymptotic normality of the estimate.The efficacy of our method is demonstrated through both simulations and a real data analysis.

关 键 词：Central subspace expectation of conditionaldifference measure sufficientdimension reduction 

分 类 号：O17[理学—数学]