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Metric Characterization of Random Variables and Random Processes
V. V. Buldygin, Kyïv Politechnic Institute, Ukraine, and Yu. V. Kozachenko, Kyïv Taras Shevchenko National University, Ukraine
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Translations of Mathematical Monographs
2000; 257 pp; hardcover
Volume: 188
ISBN-10: 0-8218-0533-9
ISBN-13: 978-0-8218-0533-6
List Price: US$103 Member Price: US$82.40
Order Code: MMONO/188

The topic covered in this book is the study of metric and other close characteristics of different spaces and classes of random variables and the application of the entropy method to the investigation of properties of stochastic processes whose values, or increments, belong to given spaces. The following processes appear in detail: pre-Gaussian processes, shot noise processes representable as integrals over processes with independent increments, quadratically Gaussian processes, and, in particular, correlogram-type estimates of the correlation function of a stationary Gaussian process, jointly strictly sub-Gaussian processes, etc.

The book consists of eight chapters divided into four parts: The first part deals with classes of random variables and their metric characteristics. The second part presents properties of stochastic processes "imbedded" into a space of random variables discussed in the first part. The third part considers applications of the general theory. The fourth part outlines the necessary auxiliary material.

Problems and solutions presented show the intrinsic relation existing between probability methods, analytic methods, and functional methods in the theory of stochastic processes. The concluding sections, "Comments" and "References", gives references to the literature used by the authors in writing the book.

Graduate students and research mathematicians interested in probability theory and stochastic processes.

Reviews

"The analytical and formal-theoretical perspective of this book could be used as a basis for future historical and quantitative studies."

-- Zentralblatt MATH

• Sub-Gaussian and pre-Gaussian random variables
• Orlicz spaces of random variables
• Regularity of sample paths of a stochastic process
• Pre-Gaussian processes
• Shot noise processes and their properties
• Correlograms of stationary Gaussian processes
• Jointly sub-Gaussian, super-Gaussian, and pseudo-Gaussian stochastic processes
• Appendices