The analysis of contingency tables under inequality constraints

Journal of Statistical Planning and InferenceVolume 107, Issues 1-2, 1 September 2002, Pages 45-73

Alan Agresti, , and Brent A. Coull

Inconsistency of the bootstrap when a parameter is on the boundary of the parameter space

Andrew, 2000, Econometrica

cowles.econ.yale.edu/~dwka/pub/p0994.pdf

Nonlinear Hypotheses, Inequality Restrictions, and Non-Nested Hypotheses

Nonlinear Hypotheses, Inequality Restrictions, and Non-Nested Hypotheses: Exact Simultaneous Tests i...
Jean-Marie Dufour
Econometrica, Vol. 57, No. 2 (Mar., 1989), pp. 335-355
Published by: The Econometric Society

The Sucess of Econometrics

The Sucess of Econometrics,
Jan R. Magnus
De Economist; Mar 1999; 147, 1

In Memory of John Denis Sargan

Econometric Theory
Special Issue devoted to John Denis Sargan

Finite Sample Properties of Bootstrap GMM

http://interstat.statjournals.net/YEAR/2010/articles/1002002.pdf

The Bootstrap’s Finite Sample Distribution

http://www.nd.edu/~meg/MEG2004/Marsh-Lawrence.pdf

FINITE SAMPLE APPROXIMATION RESULTS FOR PRINCIPAL COMPONENT ANALYSIS

http://www.wisdom.weizmann.ac.il/~nadler/Publications/pca_finite_sample_AOS.pdf

Thomas S. Ferguson: BIOGRAPHY

Biography
Source: F. Thomas Bruss, and Lucien Le Cam, eds. Game theory, optimal stopping, probability and statistics: Papers in honor of Thomas S. Ferguson (Beachwood, OH: Institute of Mathematical Statistics, 2000),

A Course in Large Sample Theory

A Course in Large Sample Theory
Chapman & Hall, 1996.Table of Contents
Part 1: Basic Probability Theory.
1. Modes of Convergence.
2. Partial Converses.
3. Convergence in Law.
4. Laws of Large Numbers.
5. Central Limit Theorems.
Part 2: Basic Statistical Large Sample Theory
6. Slutsky Theorems.
7. Functions of the Sample Moments.
8. The Sample Correlation Coefficient.
9. Pearson's Chi-Square.
10. Asymptotic Power of the Pearson Chi-Square Test.
Part 3: Special Topics.
11. Stationary m-dependent Sequences.
12. Some Rank Statistics.
13. Asymptotic Distribution of Sample Quantiles.
14. Asymptotic Theory of Extreme Order Statistics.
15. Asymptotic Joint Distributions of Extrema.
Part 4: Efficient Estimation and Testing.
16. A Uniform Strong Law of Large Numbers.
17. Strong Consistency of the Maximum Likelihood Estimates.
18. Asymptotic Normality of the MLE.
19. The Cramer-Rao Lower Bound.
20. Asymptotic Efficiency.
21. Asymptotic Normality of Posterior Distributions.
22. Asymptotic Distribution of the Likelihood Ratio Test Statistic.
23. Minimum Chi-Square Estimates.
24. General Chi-Square Tests

Asymptotic Theory in Probability and Statistics with Applications

Advanced Lectures in Mathematics, Vol. 2
Asymptotic Theory in Probability and Statistics with Applications
Edited by
Tze Leung Lai (Stanford University)
Lianfen Qian (Florida Atlantic University)
Qi-Man Shao (University of Oregon)

A collection of 18 papers, many of which are surveys, on asymptotic theory in probability and statistics, with applications to a wide variety of problems. This volume comprises three parts: limit theorems, statistics and applications, and mathematical finance and insurance. It is intended for graduate students in probability and statistics, and for researchers in related areas.