Partially Linear Models [electronic resource] / by Wolfgang Härdle, Hua Liang, Jiti Gao
- Härdle, Wolfgang
- Heidelberg : Physica-Verlag HD : Imprint: Physica, 2000.
- Physical Description:
- X, 206 pages : online resource
- Additional Creators:
- Liang, Hua, Gao, Jiti, and SpringerLink (Online service)
- Contributions to Statistics, 1431-1968
- 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.
- 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.
- Digital File Characteristics:
- text file PDF
- AVAILABLE ONLINE TO AUTHORIZED PSU USERS.
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