Convergence of Probability Measures by Patrick Billingsley (English) Hardcover B

Description: FREE SHIPPING UK WIDE Convergence of Probability Measures by Patrick Billingsley This book is about weak convergence methods in metric spaces, with applications sufficient to show their power and utility. FORMAT Hardcover LANGUAGE English CONDITION Brand New Publisher Description A new look at weak-convergence methods in metric spaces-from a master of probability theory In this new edition, Patrick Billingsley updates his classic work Convergence of Probability Measures to reflect developments of the past thirty years. Widely known for his straightforward approach and reader-friendly style, Dr. Billingsley presents a clear, precise, up-to-date account of probability limit theory in metric spaces. He incorporates many examples and applications that illustrate the power and utility of this theory in a range of disciplines-from analysis and number theory to statistics, engineering, economics, and population biology. With an emphasis on the simplicity of the mathematics and smooth transitions between topics, the Second Edition boasts major revisions of the sections on dependent random variables as well as new sections on relative measure, on lacunary trigonometric series, and on the Poisson-Dirichlet distribution as a description of the long cycles in permutations and the large divisors of integers. Assuming only standard measure-theoretic probability and metric-space topology, Convergence of Probability Measures provides statisticians and mathematicians with basic tools of probability theory as well as a springboard to the "industrial-strength" literature available today. Back Cover A new look at weak-convergence methods in metric spaces—from a master of probability theory In this new edition, Patrick Billingsley updates his classic work Convergence of Probability Measures to reflect developments of the past thirty years. Widely known for his straightforward approach and reader-friendly style, Dr. Billingsley presents a clear, precise, up-to-date account of probability limit theory in metric spaces. He incorporates many examples and applications that illustrate the power and utility of this theory in a range of disciplines—from analysis and number theory to statistics, engineering, economics, and population biology. With an emphasis on the simplicity of the mathematics and smooth transitions between topics, the Second Edition boasts major revisions of the sections on dependent random variables as well as new sections on relative measure, on lacunary trigonometric series, and on the Poisson-Dirichlet distribution as a description of the long cycles in permutations and the large divisors of integers. Assuming only standard measure-theoretic probability and metric-space topology, Convergence of Probability Measures provides statisticians and mathematicians with basic tools of probability theory as well as a springboard to the "industrial-strength" literature available today. Flap A new look at weak-convergence methods in metric spaces-from a master of probability theory In this new edition, Patrick Billingsley updates his classic work Convergence of Probability Measures to reflect developments of the past thirty years. Widely known for his straightforward approach and reader-friendly style, Dr. Billingsley presents a clear, precise, up-to-date account of probability limit theory in metric spaces. He incorporates many examples and applications that illustrate the power and utility of this theory in a range of disciplines-from analysis and number theory to statistics, engineering, economics, and population biology. With an emphasis on the simplicity of the mathematics and smooth transitions between topics, the Second Edition boasts major revisions of the sections on dependent random variables as well as new sections on relative measure, on lacunary trigonometric series, and on the Poisson-Dirichlet distribution as a description of the long cycles in permutations and the large divisors of integers. Assuming only standard measure-theoretic probability and metric-space topology, Convergence of Probability Measures provides statisticians and mathematicians with basic tools of probability theory as well as a springboard to the "industrial-strength" literature available today. Author Biography PATRICK BILLINGSLEY, PhD, is Professor of Mathematics and Statistics at the University of Chicago. His book, Probability and Measure, Third Edition, is also available from Wiley. Table of Contents Weak Convergence in Metric Spaces. The Space C. The Space D. Dependent Variables. Other Modes of Convergence. Appendix. Some Notes on the Problems. Bibliographical Notes. Bibliography. Index. Review The book is a classic--it is almost an insult to review it. This second edition will, probably and rightly, be urged on todays research students by their predecessors, now their supervisors, who derived so much from the first edition. As the author says, 30 years ago the book would take the aspiring researcher to the forefront. Now, with the huge development over these years, it just provides an initial grounding, though no less essential. (The Statistician 49 (3) 2000) ...it seems destined to become another clasic and is of interest even to those who already own the first edition. (Zentralblatt Math, Volume 944, No 19, 2000) Long Description A new look at weakconvergence methods in metric spacesfrom a master of probability theory In this new edition, Patrick Billingsley updates his classic work Convergence of Probability Measures to reflect developments of the past thirty years. Widely known for his straightforward approach and readerfriendly style, Dr. Billingsley presents a clear, precise, uptodate account of probability limit theory in metric spaces. He incorporates many examples and applications that illustrate the power and utility of this theory in a range of disciplinesfrom analysis and number theory to statistics, engineering, economics, and population biology. With an emphasis on the simplicity of the mathematics and smooth transitions between topics, the Second Edition boasts major revisions of the sections on dependent random variables as well as new sections on relative measure, on lacunary trigonometric series, and on the PoissonDirichlet distribution as a description of the long cycles in permutations and the large divisors of integers. Assuming only standard measuretheoretic probability and metricspace topology, Convergence of Probability Measures provides statisticians and mathematicians with basic tools of probability theory as well as a springboard to the "industrialstrength" literature available today. Review Text The book is a classic--it is almost an insult to review it. This second edition will, probably and rightly, be urged on todays research students by their predecessors, now their supervisors, who derived so much from the first edition. As the author says, 30 years ago the book would take the aspiring researcher to the forefront. Now, with the huge development over these years, it just provides an initial grounding, though no less essential. (The Statistician 49 (3) 2000) ...it seems destined to become another clasic and is of interest even to those who already own the first edition. (Zentralblatt Math, Volume 944, No 19, 2000) Review Quote The book is a classic [...]. (The Statistician, 49 (3), 2000) ...it seems destined to become another clasic and is of interest even to those who already own the first edition. (Zentralblatt Math, Volume 944, No. 19, 2000) "...the author may be congratulated. The book will definitely maintain and extend its role as a fundamental introduction and contribution to the subject." (Statistics & Decisions, Vol. 18/3, 2000) Promotional "Headline" The book is a classic [...]. (The Statistician, 49 (3), 2000) ...it seems destined to become another clasic and is of interest even to those who already own the first edition. (Zentralblatt Math, Volume 944, No. 19, 2000) "...the author may be congratulated. The book will definitely maintain and extend its role as a fundamental introduction and contribution to the subject." (Statistics & Decisions, Vol. 18/3, 2000) Feature Useful as a textbook that one can study before tackling the "industrial strength" treatises now available. All sections have been re-worked, clarifying some and shortening others (most notably theories on dependent random variables) by using discoveries of the last thirty years. Some new topics added (e.g. subspaces, relative measure, Skorohods Representation Theorem, The Prohorov Metric, and The Poisson Limit) and two new sections: Long Cycles and Large Divisors; Trigonometric Series. Written with students in-mind (e.g. smooth transitional writing, ease of mathematics, and thought-provoking problem sets are stressed throughout the book). Some new applications, where appropriate, to illustrate the theory as it emerges in stages. Standard measure-theoretic probability and metric-space topology assumed; no general (nonmetric) topology employed. Details ISBN0471197459 Author Patrick Billingsley Short Title CONVERGENCE OF PROBABILITY MEA Language English Edition 2nd ISBN-10 0471197459 ISBN-13 9780471197454 Media Book Format Hardcover Year 1999 Place of Publication New York Country of Publication United States Replaces 9780471072423 Alternative 9780470316962 Series Wiley Series in Probability and Statistics Series Number 316 Affiliation Univ. of Chicago The Univ. of Chicago, IL The Univ. of Chicago, Illino DOI 10.1604/9780471197454 UK Release Date 1999-08-23 AU Release Date 1999-07-16 NZ Release Date 1999-07-16 Pages 304 Publisher John Wiley & Sons Inc Edition Description 2nd edition Publication Date 1999-08-23 Imprint Wiley-Interscience DEWEY 519.2 Audience Postgraduate, Research & Scholarly US Release Date 1999-08-23 We've got this At The Nile, if you're looking for it, we've got it. 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