A PARTIALLY LINEAR FRAMEWORK FOR MASSIVE HETEROGENEOUS DATA

We consider a partially linear framework for modelling massive heterogeneous data. The major goal is to extract common features across all sub-populations while exploring heterogeneity of each sub-population. In particular, we propose an aggregation type estimator for the commonality parameter that...

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Bibliographic Details

Published in:	The Annals of statistics Vol. 44; no. 4; p. 1400
Main Authors:	Zhao, Tianqi, Cheng, Guang, Liu, Han
Format:	Journal Article
Language:	English
Published:	United States 01.08.2016
Subjects:	partially linear model joint asymptotics heterogenous data massive data mean square error reproducing kernel Hilbert space bias propagation
ISSN:	0090-5364
Online Access:	Get more information
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