Generalized additive partial linear models with high-dimensional covariates

This paper studies generalized additive partial linear models with high-dimensional covariates. We are interested in which components (including parametric and nonparametric components) are nonzero. The additive nonparametric functions are approximated by polynomial splines. We propose a doubly pena...

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Main Authors: Lian, Heng, Liang, Hua
Other Authors: School of Physical and Mathematical Sciences
Format: Journal Article
Language:English
Published: 2014
Subjects:
Online Access:https://hdl.handle.net/10356/101379
http://hdl.handle.net/10220/18668
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author Lian, Heng
Liang, Hua
author2 School of Physical and Mathematical Sciences
author_facet School of Physical and Mathematical Sciences
Lian, Heng
Liang, Hua
author_sort Lian, Heng
collection NTU
description This paper studies generalized additive partial linear models with high-dimensional covariates. We are interested in which components (including parametric and nonparametric components) are nonzero. The additive nonparametric functions are approximated by polynomial splines. We propose a doubly penalized procedure to obtain an initial estimate and then use the adaptive least absolute shrinkage and selection operator to identify nonzero components and to obtain the final selection and estimation results. We establish selection and estimation consistency of the estimator in addition to asymptotic normality for the estimator of the parametric components by employing a penalized quasi-likelihood. Thus our estimator is shown to have an asymptotic oracle property. Monte Carlo simulations show that the proposed procedure works well with moderate sample sizes.
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spelling ntu-10356/1013792023-02-28T19:41:17Z Generalized additive partial linear models with high-dimensional covariates Lian, Heng Liang, Hua School of Physical and Mathematical Sciences DRNTU::Science::Mathematics This paper studies generalized additive partial linear models with high-dimensional covariates. We are interested in which components (including parametric and nonparametric components) are nonzero. The additive nonparametric functions are approximated by polynomial splines. We propose a doubly penalized procedure to obtain an initial estimate and then use the adaptive least absolute shrinkage and selection operator to identify nonzero components and to obtain the final selection and estimation results. We establish selection and estimation consistency of the estimator in addition to asymptotic normality for the estimator of the parametric components by employing a penalized quasi-likelihood. Thus our estimator is shown to have an asymptotic oracle property. Monte Carlo simulations show that the proposed procedure works well with moderate sample sizes. Published version 2014-01-22T02:24:27Z 2019-12-06T20:37:31Z 2014-01-22T02:24:27Z 2019-12-06T20:37:31Z 2013 2013 Journal Article Lian, H., & Liang, H. (2013). Generalized additive partial linear models with high-dimensional covariates. Econometric theory, 29(6), 1136-1161. https://hdl.handle.net/10356/101379 http://hdl.handle.net/10220/18668 10.1017/S0266466613000029 en Econometric theory © 2013 Cambridge University Press. This paper was published in Econometric Theory and is made available as an electronic reprint (preprint) with permission of Cambridge University Press. The paper can be found at the following official DOI: [http://dx.doi.org/10.1017/S0266466613000029]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law. application/pdf
spellingShingle DRNTU::Science::Mathematics
Lian, Heng
Liang, Hua
Generalized additive partial linear models with high-dimensional covariates
title Generalized additive partial linear models with high-dimensional covariates
title_full Generalized additive partial linear models with high-dimensional covariates
title_fullStr Generalized additive partial linear models with high-dimensional covariates
title_full_unstemmed Generalized additive partial linear models with high-dimensional covariates
title_short Generalized additive partial linear models with high-dimensional covariates
title_sort generalized additive partial linear models with high dimensional covariates
topic DRNTU::Science::Mathematics
url https://hdl.handle.net/10356/101379
http://hdl.handle.net/10220/18668
work_keys_str_mv AT lianheng generalizedadditivepartiallinearmodelswithhighdimensionalcovariates
AT lianghua generalizedadditivepartiallinearmodelswithhighdimensionalcovariates