The aso theory developed in Chapters 8 - 12 presumes that the tan- gent cones are linear spaces. In the present chapter we collect a few natural examples where the tangent cone fails to be a linear space. These examples are to remind the reader that an extension of the theo- ry to convex tangent con
Contributions to a General Asymptotic Statistical Theory
β Scribed by J. Pfanzagl (auth.)
- Publisher
- Springer-Verlag New York
- Year
- 1982
- Tongue
- English
- Leaves
- 323
- Series
- Lecture Notes in Statistics 13
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Table of Contents
Front Matter....Pages i-vii
Introduction....Pages 1-21
The Local Structure of Families of Probability Measures....Pages 22-32
Examples of Tangent Spaces....Pages 33-56
Tangent Cones....Pages 57-64
Differentiable Functionals....Pages 65-77
Examples of Differentiable Functionals....Pages 78-89
Distance Functions for Probability Measures....Pages 90-98
Projections of Probability Measures....Pages 99-114
Asymptotic Bounds for the Power of Tests....Pages 115-149
Asymptotic Bounds for the Concentration of Estimators....Pages 150-176
Existence of Asymptotically Efficient Estimators for Probability Measures....Pages 177-195
Existence of Asymptotically Efficient Estimators for Functionals....Pages 196-210
Existence of Asymptotically Efficient Tests....Pages 211-214
Inference for Parametric Families....Pages 215-225
Random Nuisance Parameters....Pages 226-236
Inference for Symmetric Probability Measures....Pages 237-248
Inference for Measures on Product Spaces....Pages 249-257
Dependence β Independence....Pages 258-264
Two-Sample Problems....Pages 265-288
Appendix....Pages 289-299
Back Matter....Pages 300-316
β¦ Subjects
Statistics, general
π SIMILAR VOLUMES
The SM (PDF) is available for Free from Author's website http://www.ams.org/publications/authors/books/postpub/gsm-119
Free from the Author(s) Page http://www.ams.org/publications/authors/books/postpub/gsm-119
This book is designed to bridge the gap between traditional textbooks in statistics and more advanced books that include the sophisticated nonparametric techniques. It covers topics in parametric and nonparametric large-sample estimation theory. The exposition is based on a collection of relatively