Geometrical foundations of asymptotic inference /
Differential geometry provides an aesthetically appealing and often revealing view of statistical inference. Beginning with an elementary treatment of one-parameter statistical models and ending with an overview of recent developments, this is the first book to provide an introduction to the subject...
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| Format: | eBook |
| Language: | English |
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New York :
Wiley,
1997.
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| Online Access: | Connect to the full text of this electronic book |
Table of Contents:
- Front Matter
- Overview and Preliminaries
- One-Parameter Curved Exponential Families. First-Order Asymptotics
- Second-Order Asymptotics
- Multiparameter Curved Exponential Families. Extensions of Results from the One-Parameter Case
- Exponential Family Regression and Diagnostics
- Curvature in Exponential Family Regression
- Differential-Geometric Methods. Information-Metric Riemannian Geometry
- Statistical Manifolds
- Divergence Functions
- Recent Developments
- Appendix A: Diffeomorphisms and the Inverse Function Theorem
- Appendix B: Arclength and Curvature of Curves
- Appendix C: Basic Concepts in Differential Geometry
- Appendix D: A Coordinate-Free Definition of Weak Sphericity
- References
- Symbol Index
- Index
- Wiley Series in Probability and Statistics.
- One-parameter curved exponential familes
- First-order asymptotics
- Second-order asymptotics
- Multiparameter curved exponential families
- Exponential family regression and diagnostics
- Curvature in exponential family regression
- Differential-geometric methods
- Information-metric riemannian geometry
- Sttistical manifolds
- Divergence functions
- Recent developments.