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Partially Linear Models
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Catalogue Information
Field name
Details
Dewey Class
519.2
Title
Partially Linear Models ([EBook]) / by Wolfgang Härdle, Hua Liang, Jiti Gao.
Author
Härdle, Wolfgang. , 1953-
Added Personal Name
Liang, Hua
Gao, Jiti
Other name(s)
SpringerLink (Online service)
Publication
Heidelberg : Physica-Verlag HD , 2000.
Physical Details
X, 206 pages : online resource.
Series
Contributions to Statistics
1431-1968
ISBN
9783642577000
Summary Note
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.:
Contents note
1 Introduction -- 2 Estimation of The Parametric Component -- 3 Estimation of The Nonparametric Component -- 4 Estimation with Measurement Errors -- 5 Some Related Theoretic Topics -- 6 Partially Linear Time Series Models -- Appendix: Basic Lemmas -- Author Index -- Symbols and Notation.
System details note
Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users)
Internet Site
http://dx.doi.org/10.1007/978-3-642-57700-0
Links to Related Works
Subject References:
Econometrics
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Mathematics
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Probabilities
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Probability theory and stochastic processes
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Statistical Theory and Methods
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Statistics
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Authors:
author
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Gao, Jiti
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Härdle, Wolfgang. 1953-
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Härdle, Wolfgang, 1953-
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Liang, Hua
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Corporate Authors:
SpringerLink (Online service)
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Series:
Contributions to Statistics
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Classification:
519.2
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