This book is an encyclopedic treatment of classic as well as contemporary large sample theory, dealing with both statistical problems and probabilistic issues and tools. It is written in an extremely lucid style, with an emphasis on the conceptual discussion of the importance of a problem and the impact and relevance of the theorems. The book has 34 chapters over a wide range of topics,nearly 600 exercises for practice and instruction, and another 300 worked outexamples. It also includes a large compendium of 300 useful inequalities on probability, linear algebra, and analysis that are collected together from numerous sources, as an invaluable reference for researchers in statistics, probability, and mathematics. Encyclopedic coverage of classical topics and at the same time of some of the most modern topics. Versatile research reference to anyone working on theoretical statistics and probability. Emphasis on presentingthe material in a lucid and accessible style, suitable for conceptual understanding of a very broad range of topics. INDICE: From the contents Basic Convergence Concepts and Theorems. Metrics, Information Theory, Convergence, and Poisson Approximations. More General Weak and Strong Laws and the Delta Theorem. Transformations. More General Clts. Moment Convergence and Uniform Integrability. Sample Percentiles and Order Statistics. Sample Extremes. Central Limit theorems for Dependent Sequences. Central Limit Theorem for Markov Chains. Accuracy of Clts. Invariance Principles. Edgeworth Expansions and Cumulants. Saddlepoint Approximations. U-Statistics. Maximum Likelihood Estimates. M Estimates. the Trimmed Mean.-
- ISBN: 978-0-387-75970-8
- Editorial: Springer
- Encuadernacion: Cartoné
- Páginas: 695
- Fecha Publicación: 01/04/2008
- Nº Volúmenes: 1
- Idioma: Inglés