Nonparametric Statistics for Stochastic Processes : Estimation and Prediction /
This book is devoted to the theory and applications of nonparametic functional estimation and prediction. Chapter 1 provides an overview of inequalities and limit theorems for strong mixing processes. Density and regression estimation in discrete time are studied in Chapter 2 and 3. The special rate...
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| Format: | eBook |
| Language: | English |
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New York, NY :
Springer New York,
1998.
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| Edition: | Second edition. |
| Series: | Lecture notes in statistics (Springer-Verlag) ;
110. |
| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
Table of Contents:
- Inequalities for Mixing Processes
- Density Estimation for Discrete Time Processes
- Regression Estimation and Prediction for Discrete Time Processes
- Kernel Density Estimation for Continuous Time Processes
- Regression Estimation and Prediction in Continuous Time
- The Local Time Density Estimator
- Implementation of Nonparametric Method and Numerical Appliations.