An Introduction to Stochastic Processes and Their Applications (Record no. 81723)

000 -LEADER
fixed length control field 07073nam a22005535i 4500
001 - CONTROL NUMBER
control field 978-1-4613-9742-7
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20221102211609.0
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 121227s1992 xxu| s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781461397427
-- 978-1-4613-9742-7
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-1-4613-9742-7
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA273.A1-274.9
072 #7 - SUBJECT CATEGORY CODE
Subject category code PBT
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code PBWL
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code MAT029000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code PBT
Source thema
072 #7 - SUBJECT CATEGORY CODE
Subject category code PBWL
Source thema
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.2
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Todorovic, Petar.
Relator term author.
Relationship aut
-- http://id.loc.gov/vocabulary/relators/aut
9 (RLIN) 66786
245 13 - TITLE STATEMENT
Title An Introduction to Stochastic Processes and Their Applications
Medium [electronic resource] /
Statement of responsibility, etc. by Petar Todorovic.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 1992.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture New York, NY :
Name of producer, publisher, distributor, manufacturer Springer New York :
-- Imprint: Springer,
Date of production, publication, distribution, manufacture, or copyright notice 1992.
300 ## - PHYSICAL DESCRIPTION
Extent XIV, 289 p.
Other physical details online resource.
336 ## - CONTENT TYPE
Content type term text
Content type code txt
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337 ## - MEDIA TYPE
Media type term computer
Media type code c
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term online resource
Carrier type code cr
Source rdacarrier
347 ## - DIGITAL FILE CHARACTERISTICS
File type text file
Encoding format PDF
Source rda
490 1# - SERIES STATEMENT
Series statement Springer Series in Statistics,
International Standard Serial Number 2197-568X
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note 1 Basic Concepts and Definitions -- 1.1. Definition of a Stochastic Process -- 1.2. Sample Functions -- 1.3. Equivalent Stochastic Processes -- 1.4. Kolmogorov Construction -- 1.5. Principal Classes of Random Processes -- 1.6. Some Applications -- 1.7. Separability -- 1.8. Some Examples -- 1.9. Continuity Concepts -- 1.10. More on Separability and Continuity -- 1.11. Measurable Random Processes -- Problems and Complements -- 2 The Poisson Process and Its Ramifications -- 2.1. Introduction -- 2.2. Simple Point Process on R+ -- 2.3. Some Auxiliary Results -- 2.4. Definition of a Poisson Process -- 2.5. Arrival Times ?k -- 2.6. Markov Property of N(t) and Its Implications -- 2.7. Doubly Stochastic Poisson Process -- 2.8. Thinning of a Point Process -- 2.9. Marked Point Processes -- 2.10. Modeling of Floods -- Problems and Complements -- 3 Elements of Brownian Motion -- 3.1. Definitions and Preliminaries -- 3.2. Hitting Times -- 3.3. Extremes of ?(t) -- 3.4. Some Properties of the Brownian Paths -- 3.5. Law of the Iterated Logarithm -- 3.6. Some Extensions -- 3.7. The Ornstein-Uhlenbeck Process -- 3.8. Stochastic Integration -- Problems and Complements -- 4 Gaussian Processes -- 4.1. Review of Elements of Matrix Analysis -- 4.2. Gaussian Systems -- 4.3. Some Characterizations of the Normal Distribution -- 4.4. The Gaussian Process -- 4.5. Markov Gaussian Process -- 4.6. Stationary Gaussian Process -- Problems and Complements -- 5 L2 Space -- 5.1. Definitions and Preliminaries -- 5.2. Convergence in Quadratic Mean -- 5.3. Remarks on the Structure of L2 -- 5.4. Orthogonal Projection -- 5.5. Orthogonal Basis -- 5.6. Existence of a Complete Orthonormal Sequence in L2 -- 5.7. Linear Operators in a Hilbert Space -- 5.8. Projection Operators -- Problems and Complements -- 6 Second-Order Processes -- 6.1. Covariance Function C(s,t) -- 6.2. Quadratic Mean Continuity and Differentiability -- 6.3. Eigenvalues and Eigenfunctions of C(s, t) -- 6.4. Karhunen-Loeve Expansion -- 6.5. Stationary Stochastic Processes -- 6.6. Remarks on the Ergodicity Property -- Problems and Complements -- 7 Spectral Analysis of Stationary Processes -- 7.1. Preliminaries -- 7.2. Proof of the Bochner-Khinchin and Herglotz Theorems -- 7.3. Random Measures -- 7.4. Process with Orthogonal Increments -- 7.5. Spectral Representation -- 7.6. Ramifications of Spectral Representation -- 7.7. Estimation, Prediction, and Filtering -- 7.8. An Application -- 7.9. Linear Transformations -- 7.10. Linear Prediction, General Remarks -- 7.11. The Wold Decomposition -- 7.12. Discrete Parameter Processes -- 7.13. Linear Prediction -- 7.14. Evaluation of the Spectral Characteristic ?(?, h) -- 7.15. General Form of Rational Spectral Density -- Problems and Complements -- 8 Markov Processes I -- 8.1. Introduction -- 8.2. Invariant Measures -- 8.3. Countable State Space -- 8.4. Birth and Death Process -- 8.5. Sample Function Properties -- 8.6. Strong Markov Processes -- 8.7. Structure of a Markov Chain -- 8.8. Homogeneous Diffusion -- Problems and Complements -- 9 Markov Processes II: Application of Semigroup Theory -- 9.1. Introduction and Preliminaries -- 9.2. Generator of a Semigroup -- 9.3. The Resolvent -- 9.4. Uniqueness Theorem -- 9.5. The Hille-Yosida Theorem -- 9.6. Examples -- 9.7. Some Refinements and Extensions -- Problems and Complements -- 10 Discrete Parameter Martingales -- 10.1. Conditional Expectation -- 10.2. Discrete Parameter Martingales -- 10.3. Examples -- 10.4. The Upcrossing Inequality -- 10.5. Convergence of Submartingales -- 10.6. Uniformly Integrable Martingales -- Problems and Complements.
520 ## - SUMMARY, ETC.
Summary, etc. This text on stochastic processes and their applications is based on a set of lectures given during the past several years at the University of California, Santa Barbara (UCSB). It is an introductory graduate course designed for classroom purposes. Its objective is to provide graduate students of statistics with an overview of some basic methods and techniques in the theory of stochastic processes. The only prerequisites are some rudiments of measure and integration theory and an intermediate course in probability theory. There are more than 50 examples and applications and 243 problems and complements which appear at the end of each chapter. The book consists of 10 chapters. Basic concepts and definitions are pro­ vided in Chapter 1. This chapter also contains a number of motivating ex­ amples and applications illustrating the practical use of the concepts. The last five sections are devoted to topics such as separability, continuity, and measurability of random processes, which are discussed in some detail. The concept of a simple point process on R+ is introduced in Chapter 2. Using the coupling inequality and Le Cam's lemma, it is shown that if its counting function is stochastically continuous and has independent increments, the point process is Poisson. When the counting function is Markovian, the sequence of arrival times is also a Markov process. Some related topics such as independent thinning and marked point processes are also discussed. In the final section, an application of these results to flood modeling is presented.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Probabilities.
9 (RLIN) 4604
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Statistics .
9 (RLIN) 31616
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Probability Theory.
9 (RLIN) 17950
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Statistics.
9 (RLIN) 14134
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
9 (RLIN) 66787
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9781461397441
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9780387977836
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9781461397434
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Springer Series in Statistics,
International Standard Serial Number 2197-568X
9 (RLIN) 66788
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-1-4613-9742-7">https://doi.org/10.1007/978-1-4613-9742-7</a>
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Koha item type eTextbook

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