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Probability Theory - Independence, Interchangeability, Martingales (Hardcover, 3rd ed. 1997): Yuan Shih Chow, Henry Teicher Probability Theory - Independence, Interchangeability, Martingales (Hardcover, 3rd ed. 1997)
Yuan Shih Chow, Henry Teicher
R2,703 Discovery Miles 27 030 Ships in 18 - 22 working days

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.

Probability Theory - Independence, Interchangeability, Martingales (Paperback, 3rd ed. 1997): Yuan Shih Chow, Henry Teicher Probability Theory - Independence, Interchangeability, Martingales (Paperback, 3rd ed. 1997)
Yuan Shih Chow, Henry Teicher
R1,871 R1,636 Discovery Miles 16 360 Save R235 (13%) Ships in 10 - 15 working days

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.

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