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Author Ferguson, Thomas S. (Thomas Shelburne), 1929- author

Title A course in large sample theory / Thomas S. Ferguson
Edition First edition
Published London : Chapman & Hall, 1996
London : Chapman & Hall, 2002


Location Call no. Vol. Availability
 W'PONDS  519.52 Fer/Cil  AVAILABLE
Description 245 pages : illustrations ; 24 cm
Series Chapman & Hall texts in statistical science
Texts in statistical science.
Contents Pt. 1. Basic Probability. 1. Modes of Convergence. 2. Partial Converses to Theorem 1. 3. Convergence in Law. 4. Laws of Large Numbers. 5. Central Limit Theorems -- Pt. 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 -- Pt. 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 -- Pt. 4. Efficient Estimation and Testing. 16. A Uniform Strong Law of Large Numbers. 17. Strong Consistency of Maximum-Likelihood Estimates. 18. Asymptotic Normality of the Maximum-Likelihood Estimate. 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
Analysis Statistics
Notes Bibliography: p236-237. - Includes index
Bibliography Includes bibliographical references (pages 236-239) and index
Subject Asymptotic distribution (Probability theory)
Law of large numbers.
Sampling (Statistics)
LC no. 96086138
ISBN 0412043718