Probability theory, random processes and mathematical statistics
Author(s)
Bibliographic Information
Probability theory, random processes and mathematical statistics
（Mathematics and its applications, v. 344）
Kluwer Academic Publishers, c1995
- Other Title
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Teorii︠a︡ veroi︠a︡tnosteĭ, sluchaĭnye prot︠s︡essy i matematicheskai︠a︡ statistika
Available at 28 libraries
Note
Includes index
Description and Table of Contents
Description
Probability Theory, Theory of Random Processes and Mathematical Statistics are important areas of modern mathematics and its applications. They develop rigorous models for a proper treatment for various 'random' phenomena which we encounter in the real world. They provide us with numerous tools for an analysis, prediction and, ultimately, control of random phenomena. Statistics itself helps with choice of a proper mathematical model (e.g., by estimation of unknown parameters) on the basis of statistical data collected by observations. This volume is intended to be a concise textbook for a graduate level course, with carefully selected topics representing the most important areas of modern Probability, Random Processes and Statistics. The first part (Ch. 1-3) can serve as a self-contained, elementary introduction to Probability, Random Processes and Statistics. It contains a number of relatively sim ple and typical examples of random phenomena which allow a natural introduction of general structures and methods. Only knowledge of elements of real/complex analysis, linear algebra and ordinary differential equations is required here. The second part (Ch. 4-6) provides a foundation of Stochastic Analysis, gives information on basic models of random processes and tools to study them. Here a familiarity with elements of functional analysis is necessary. Our intention to make this course fast-moving made it necessary to present important material in a form of examples.
Table of Contents
Preface. Annotation. 1. Introductory probability theory. 2. Random processes. 3. An introduction to mathematical statistics. 4. Basic elements of probability theory. 5. Elements of stochastic analysis and stochastic differential equations. Subject index.
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