Introduction to Empirical Processes and Semiparametric Inference
This book provides a self-contained, linear, and unified introduction to empirical processes and semiparametric inference. These powerful research techniques are surprisingly useful for developing methods of statistical inference for complex models and in understanding the properties of such methods...
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| Language: | English |
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New York, NY :
Springer New York : Imprint: Springer,
2008.
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| Edition: | 1st ed. 2008. |
| Series: | Springer Series in Statistics,
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| Online Access: | https://doi.org/10.1007/978-0-387-74978-5 |
Table of Contents:
- Overview
- An Overview of Empirical Processes
- Overview of Semiparametric Inference
- Case Studies I
- Empirical Processes
- to Empirical Processes
- Preliminaries for Empirical Processes
- Stochastic Convergence
- Empirical Process Methods
- Entropy Calculations
- Bootstrapping Empirical Processes
- Additional Empirical Process Results
- The Functional Delta Method
- Z-Estimators
- M-Estimators
- Case Studies II
- Semiparametric Inference
- to Semiparametric Inference
- Preliminaries for Semiparametric Inference
- Semiparametric Models and Efficiency
- Efficient Inference for Finite-Dimensional Parameters
- Efficient Inference for Infinite-Dimensional Parameters
- Semiparametric M-Estimation
- Case Studies III.