Partially Linear Models

In the last ten years, there has been increasing interest and activity in the general area of partially linear regression smoothing in statistics. Many methods and techniques have been proposed and studied. This monograph hopes to bring an up-to-date presentation of the state of the art of partially...

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Main Authors: Härdle, Wolfgang, Liang, Hua (Author), Gao, Jiti (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Heidelberg Physica-Verlag HD 2000, 2000
Edition:1st ed. 2000
Series:Contributions to Statistics
Subjects:
Online Access:
Collection: Springer Book Archives -2004 - Collection details see MPG.ReNa
Summary:In the last ten years, there has been increasing interest and activity in the general area of partially linear regression smoothing in statistics. Many methods and techniques have been proposed and studied. This monograph hopes to bring an up-to-date presentation of the state of the art of partially linear regression techniques. The emphasis is on methodologies rather than on the theory, with a particular focus on applications of partially linear regression techniques to various statistical problems. These problems include least squares regression, asymptotically efficient estimation, bootstrap resampling, censored data analysis, linear measurement error models, nonlinear measurement models, nonlinear and nonparametric time series models
Physical Description:X, 206 p online resource
ISBN:9783642577000