Large deviation techniques in decision, simulation, and estimation - Info and Reading Options
By James A. Bucklew
"Large deviation techniques in decision, simulation, and estimation" was published by Wiley in 1990 - New York, it has 290 pages and the language of the book is English.
“Large deviation techniques in decision, simulation, and estimation” Metadata:
- Title: ➤ Large deviation techniques in decision, simulation, and estimation
- Author: James A. Bucklew
- Language: English
- Number of Pages: 290
- Publisher: Wiley
- Publish Date: 1990
- Publish Location: New York
“Large deviation techniques in decision, simulation, and estimation” Subjects and Themes:
- Subjects: Large deviations - Statistical decision - Statistics
Edition Specifications:
- Format: Hardcover
- Weight: 1 pounds
- Pagination: xiv, 270 p. :
Edition Identifiers:
- The Open Library ID: OL2226939M - OL4810877W
- Online Computer Library Center (OCLC) ID: 20825080
- Library of Congress Control Number (LCCN): 89077144
- ISBN-13: 9780471618560
- ISBN-10: 047161856X
- All ISBNs: 047161856X - 9780471618560
AI-generated Review of “Large deviation techniques in decision, simulation, and estimation”:
"Large deviation techniques in decision, simulation, and estimation" Table Of Contents:
- 1- - Cramir's Theorem and Extensions;
- 2- - Sanov's Theorem and the Contraction Principle;
- 3- - Gaussian Processes and Wentzell-Freidlin Theory;
- 4- - Large Deviations for Markov Processes;
- 5- - Applications to Detection Theory;
- 6- - Asymptotic Expansions;
- 7- - Quick Simulation;
- 8- - Applications to Parameter Estimation;
- 9- - Applications to Information Theory;
- 10- - Appendices;
- 11- - Solutions to Exercises;
- 12- - References;
- 13- - Index.
"Large deviation techniques in decision, simulation, and estimation" Description:
The Open Library:
Large deviation theory is a branch of probability concerned with explaining the behavior of certain types of rare events. Large Deviation Techniques in Decision, Simulation, and Estimation is an introductory level exposition for a nonmathematical audience of the major results and techniques available in this area. It is excellent for applied statisticians, communications engineers, statistical signal processors, information theorists, and even large deviation theorists interested in the major application areas of their field. Applications of large deviation theory are stressed throughout with entire chapters devoted to hypothesis testing, parameter estimation, fast simulation methodologies, and information theory. In a relaxed fashion, it introduces most of the major ideas and models of the subject. In addition, several new results are presented in various application areas.
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