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Lévy Processes and Infinitely Divisible Distributions Sato Paperback 2e

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L\u00E9vy Processes and Infinitely Divisible Distributions

A corrected edition of a highly successful introductory text for graduate students. Assumes no prior knowledge of stochastic processes.

Ken-iti Sato (Author)

9781107656499, Cambridge University Press

Paperback, published 19 December 2013

536 pages

22.6 x 15.2 x 3 cm, 0.76 kg

L\u00E9vy processes are rich mathematical objects and constitute perhaps the most basic class of stochastic processes with a continuous time parameter. This book is intended to provide the reader with comprehensive basic knowledge of L\u00E9vy processes, and at the same time serve as an introduction to stochastic processes in general. No specialist knowledge is assumed and proofs are given in detail. Systematic study is made of stable and semi-stable processes, and the author gives special emphasis to the correspondence between L\u00E9vy processes and infinitely divisible distributions. All serious students of random phenomena will find]

Lévy Processes and Infinitely Divisible Distributions Sato Paperback 2e

L\u00E9vy Processes and Infinitely Divisible Distributions

A corrected edition of a highly successful introductory text for graduate students. Assumes no prior knowledge of stochastic processes.

Ken-iti Sato (Author)

9781107656499, Cambridge University Press

Paperback, published 19 December 2013

536 pages

22.6 x 15.2 x 3 cm, 0.76 kg

L\u00E9vy processes are rich mathematical objects and constitute perhaps the most basic class of stochastic processes with a continuous time parameter. This book is intended to provide the reader with comprehensive basic knowledge of L\u00E9vy processes, and at the same time serve as an introduction to stochastic processes in general. No specialist knowledge is assumed and proofs are given in detail. Systematic study is made of stable and semi-stable processes, and the author gives special emphasis to the correspondence between L\u00E9vy processes and infinitely divisible distributions. All serious students of random phenomena will find]

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