publication . Preprint . Article . 2020

Semiparametric Mixtures of Regressions with Single-index for Model Based Clustering

Sijia Xiang; Weixin Yao;
Open Access English
  • Published: 23 Apr 2020
Abstract
In this article, we propose two classes of semiparametric mixture regression models with single-index for model based clustering. Unlike many semiparametric/nonparametric mixture regression models that can only be applied to low dimensional predictors, the new semiparametric models can easily incorporate high dimensional predictors into the nonparametric components. The proposed models are very general, and many of the recently proposed semiparametric/nonparametric mixture regression models are indeed special cases of the new models. Backfitting estimates and the corresponding modified EM algorithms are proposed to achieve optimal convergence rates for both para...
Subjects
arXiv: Statistics::TheoryStatistics::MethodologyStatistics::ApplicationsStatistics::Machine Learning
free text keywords: Statistics - Methodology, Applied Mathematics, Computer Science Applications, High dimensional, Convergence (routing), Model based clustering, Parametric statistics, Nonparametric statistics, Mathematics, Identifiability, Mixture regression
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