Large Deviations Techniques and Applications (Record no. 111489)

000 -LEADER
fixed length control field 03985nam a22004935i 4500
001 - CONTROL NUMBER
control field 978-3-642-03311-7
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20140220084525.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 100301s2010 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783642033117
-- 978-3-642-03311-7
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-642-03311-7
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number Q295
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA402.3-402.37
072 #7 - SUBJECT CATEGORY CODE
Subject category code GPFC
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code SCI064000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code TEC004000
Source bisacsh
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Dembo, Amir.
Relator term author.
245 10 - TITLE STATEMENT
Title Large Deviations Techniques and Applications
Medium [electronic resource] /
Statement of responsibility, etc by Amir Dembo, Ofer Zeitouni.
264 #1 -
-- Berlin, Heidelberg :
-- Springer Berlin Heidelberg,
-- 2010.
300 ## - PHYSICAL DESCRIPTION
Extent XVI, 396p.
Other physical details online resource.
336 ## -
-- text
-- txt
-- rdacontent
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-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
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490 1# - SERIES STATEMENT
Series statement Stochastic Modelling and Applied Probability,
International Standard Serial Number 0172-4568 ;
Volume number/sequential designation 38
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note LDP for Finite Dimensional Spaces -- Applications-The Finite Dimensional Case -- General Principles -- Sample Path Large Deviations -- The LDP for Abstract Empirical Measures -- Applications of Empirical Measures LDP.
520 ## - SUMMARY, ETC.
Summary, etc The theory of large deviations deals with the evaluation, for a family of probability measures parameterized by a real valued variable, of the probabilities of events which decay exponentially in the parameter. Originally developed in the context of statistical mechanics and of (random) dynamical systems, it proved to be a powerful tool in the analysis of systems where the combined effects of random perturbations lead to a behavior significantly different from the noiseless case. The volume complements the central elements of this theory with selected applications in communication and control systems, bio-molecular sequence analysis, hypothesis testing problems in statistics, and the Gibbs conditioning principle in statistical mechanics. Starting with the definition of the large deviation principle (LDP), the authors provide an overview of large deviation theorems in ${{\rm I\!R}}^d$ followed by their application. In a more abstract setup where the underlying variables take values in a topological space, the authors provide a collection of methods aimed at establishing the LDP, such as transformations of the LDP, relations between the LDP and Laplace's method for the evaluation for exponential integrals, properties of the LDP in topological vector spaces, and the behavior of the LDP under projective limits. They then turn to the study of the LDP for the sample paths of certain stochastic processes and the application of such LDP's to the problem of the exit of randomly perturbed solutions of differential equations from the domain of attraction of stable equilibria. They conclude with the LDP for the empirical measure of (discrete time) random processes: Sanov's theorem for the empirical measure of an i.i.d. sample, its extensions to Markov processes and mixing sequences and their application. The present soft cover edition is a corrected printing of the 1998 edition. Amir Dembo is a Professor of Mathematics and of Statistics at Stanford University. Ofer Zeitouni is a Professor of Mathematics at the Weizmann Institute of Science and at the University of Minnesota.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Mathematics.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Systems theory.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Distribution (Probability theory).
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Mathematics.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Systems Theory, Control.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Probability Theory and Stochastic Processes.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Zeitouni, Ofer.
Relator term author.
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer eBooks
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783642033100
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Stochastic Modelling and Applied Probability,
-- 0172-4568 ;
Volume number/sequential designation 38
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-3-642-03311-7
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