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Activity Number: 668
Type: Invited
Date/Time: Thursday, August 4, 2016 : 10:30 AM to 12:20 PM
Sponsor: IMS
Abstract #318289 View Presentation
Title: Semiparametric High-Dimensional Partial Linear Models: Estimation and Inference
Author(s): Michael Levine* and Lawrence D. Brown and Lie Wang
Companies: Purdue University and University of Pennsylvania and MIT
Keywords: semiparametric model ; multidimensional ; parametric component testing ; adaptive ; functional component estimation
Abstract:

A testing and inference problem for the multidimensional semiparametric partial linear model is considered. First, we estimate the linear component. We also obtain a new test result for the linear component whose asymptotic power does not depend on the functional component. The proposed testing procedure is easy to implement numerically. We also study its numerical performance using simulated data. Finally, we also show that a functional component can be estimated adaptively over a wide range of functional spaces.


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