Now available in paperback. This is a text comprising the major theorems of probability theory and the measure theoretical foundations of the subject. The main topics treated are independence, interchangeability,and martingales; particular emphasis is placed upon stopping times, both as tools in proving theorems and as objects of interest themselves. No prior knowledge of measure theory is assumed and a unique feature of the book is the combined presentation of measure and probability. It is easily adapted for graduate students familar with measure theory as indicated by the guidelines in the preface. Special features include: A comprehensive treatment of the law of the iterated logarithm; the Marcinklewicz-Zygmund inequality, its extension to martingales and applications thereof; development and applications of the second moment analogue of Wald's equation; limit theorems for martingale arrays, the central limit theorem for the interchangeable and martingale cases, moment convergence in the central limit theorem; complete discussion, including central limit theorem, of the random casting of r balls into n cells; recent martingale inequalities; Cram r-L vy theore and factor-closed families of distributions. This edition includes a section dealing with U-statistic, adds additional theorems and examples, and includes simpler versions of some proofs.
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Hardcover. Condition: Very Good. Hardcover. Springer Verlag. 1997. 489 pages. Springer Texts in Statistics. Third Edition. Issued in pictoral boards. No ownership marks present. Text is clean and free of marks, binding tight and solid, boards clean with no wear present. Comprising the major theorems of probability theory and the measure theoretical foundations of the subject, the main topics treated here are independence, interchangeability, and martingales. Particular emphasis is placed upon stopping times, both as tools in proving theorems and as objects of interest themselves. No prior knowledge of measure theory is assumed and a unique feature of the book is the combined presentation of measure and probability. It is easily adapted for graduate students familiar with measure theory using the guidelines given. E-79; Springer Texts in Statistics; 8vo 8" - 9" tall; 488 pages. Seller Inventory # 61804
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Hardcover. Condition: new. Hardcover. This textbook, aimed at graduate students and researchers, comprises the major theorems of probability theory and the measure theoretical foundations of the subject. The main topics treated are independence, interchangeability and martingales, with particular emphasis placed on stopping times, both as tools in providing theorems and as objects of interest themselves. This new edition also contains material on U-statistic, additional theorems and examples and simpler versions of some proofs. No prior knowledge of measure theory is assumed. limit theorems for martingale arrays, the central limit theorem for the interchangeable and martingale cases, moment convergence in the central limit theorem; complete discussion, including central limit theorem, of the random casting of r balls into n cells; Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780387982281
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Comprising the major theorems of probability theory and the measure theoretical foundations of the subject, the main topics treated here are independence, interchangeability, and martingales. Particular emphasis is placed upon stopping times, both as tools in proving theorems and as objects of interest themselves. No prior knowledge of measure theory is assumed and a unique feature of the book is the combined presentation of measure and probability. It is easily adapted for graduate students familiar with measure theory using the guidelines given.Special features include: A comprehensive treatment of the law of the iterated logarithm The Marcinklewicz-Zygmund inequality, its extension to martingales and applications thereof Development and applications of the second moment analogue of Walds equation Limit theorems for martingale arrays; the central limit theorem for the interchangeable and martingale cases; moment convergence in the central limit theorem Complete discussion, including central limit theorem, of the random casting of r balls into n cells Recent martingale inequalities Cram r-L vy theorem and factor-closed families of distributions. 516 pp. Englisch. Seller Inventory # 9780387982281
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