Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.jmva.2005.11.005
Title: Semi-parametric estimation of partially linear single-index models
Authors: Xia, Y. 
Härdle, W.
Keywords: Asymptotic distribution
Generalized partially linear model
Local linear smoother
Optimal consistency rate
Single-index model
Issue Date: May-2006
Citation: Xia, Y., Härdle, W. (2006-05). Semi-parametric estimation of partially linear single-index models. Journal of Multivariate Analysis 97 (5) : 1162-1184. ScholarBank@NUS Repository. https://doi.org/10.1016/j.jmva.2005.11.005
Abstract: One of the most difficult problems in applications of semi-parametric partially linear single-index models (PLSIM) is the choice of pilot estimators and complexity parameters which may result in radically different estimators. Pilot estimators are often assumed to be root- n consistent, although they are not given in a constructible way. Complexity parameters, such as a smoothing bandwidth are constrained to a certain speed, which is rarely determinable in practical situations. In this paper, efficient, constructible and practicable estimators of PLSIMs are designed with applications to time series. The proposed technique answers two questions from Carroll et al. [Generalized partially linear single-index models, J. Amer. Statist. Assoc. 92 (1997) 477-489]: no root- n pilot estimator for the single-index part of the model is needed and complexity parameters can be selected at the optimal smoothing rate. The asymptotic distribution is derived and the corresponding algorithm is easily implemented. Examples from real data sets (credit-scoring and environmental statistics) illustrate the technique and the proposed methodology of minimum average variance estimation (MAVE). © 2005 Elsevier Inc. All rights reserved.
Source Title: Journal of Multivariate Analysis
URI: http://scholarbank.nus.edu.sg/handle/10635/105352
ISSN: 0047259X
DOI: 10.1016/j.jmva.2005.11.005
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

126
checked on Jun 19, 2018

WEB OF SCIENCETM
Citations

120
checked on Jun 12, 2018

Page view(s)

29
checked on May 18, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.