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|a Kashyap, Rangasami L.
|q (Rangasami Laksminarayana),
|d 1938-
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|a Dynamic stochastic models from empirical data /
|c R.L. Kashyap, A. Ramachandra Rao.
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|a New York :
|b Academic Press,
|c 1976.
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|a 1 online resource (xvi, 334 pages) :
|b illustrations
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
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|a Mathematics in science and engineering ;
|v v. 122
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|a Includes bibliographical references (pages 325-330) and index.
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|a Print version record.
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|3 Use copy
|f Restrictions unspecified
|2 star
|5 MiAaHDL
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|a Electronic reproduction.
|b [Place of publication not identified] :
|c HathiTrust Digital Library,
|d 2010.
|5 MiAaHDL
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|a Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002.
|u http://purl.oclc.org/DLF/benchrepro0212
|5 MiAaHDL
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|a digitized
|c 2010
|h HathiTrust Digital Library
|l committed to preserve
|2 pda
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|a Front Cover; Dynamic Stochastic Models from Empirical Data; Copyright Page; Contents; Preface; Acknowledgments; Notation and Symbols; CHAPTER I. INTRODUCTION TO THE CONSTRUCTION OF MODELS; 1a. Nature and Goals of Modeling; 1b. Description of Models; 1c. Choice of a Model for the Given Data; 1d. Validation; Notes; CHAPTER II. PRELIMINARY ANALYSIS OF STOCHASTIC DYNAMICAL SYSTEMS; Introduction; 2a. Assumptions and Discussion; 2b. Stationarity; 2c. Invertibility; 2d. Covariance Functions and Correlograms; 2e. Spectral Analysis; 2f. Prediction; 2g. Prediction in Multiplicative Systems
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|a 2h. Prediction in Systems with Noisy Observations2i. Rescaled Range-Lag Characteristic; 2j. Fractional Noise Models; 2k. Conclusions; Appendix 2.1. Characteristics of Fractional Noise Models; Problems; CHAPTER III. STRUCTURE OF UNIVARIATE MODELS; Introduction; 3a. Types of Dynamic Stochastic Models; 3b. Types of Empirical Time Series; 3c. Causality; 3d. Choice of Time Scale for Modeling; 3e. Conclusions; Notes; Problems; CHAPTER IV. ESTIMABILITY IN SINGLE OUTPUT SYSTEMS; Introduction; 4a. Estimability of Systems in Standard Form; 4b. Estimability in Systems with Noisy Observations
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|a 4c. Estimability in Systems with AR Disturbances4d. The Estimation Accuracy; 4e. Conclusions; Appendix 4.1; Appendix 4.2. Evaluation of the Cramér-Rao Matrix Lower Bound in Single Output Systems; Problems; CHAPTER V. STRUCTURE AND ESTIMABILITY IN MULTIVARIATE SYSTEMS; Introduction; 5a. Characterization; 5b. The Triangular Canonical Forms; 5c. Diagonal Canonical Forms; 5d. Pseudocanonical Forms; 5e. Discussion of the Three Canonical Forms; 5f. Estimation Accuracy; 5g. Conclusions; Appendix 5.1. Proofs of Theorems; Problems; CHAPTER VI. ESTIMATION IN AUTOREGRESSIVE PROCESSES; Introduction
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|a 6a. Maximum Likelihood Estimators6b. Bayesian Estimators; 6c. Quasi-Maximum Likelihood (QML) Estimators in Single Output Systems; 6d. Computational Methods; 6e. Combined Parameter Estimation and Prediction; 6f. Systems with Slowly Varying Coefficients; 6g. Robust Estimation in AR Models; 6h. Conclusions; Appendix 6.1. Proofs of Theorems in Section 6a; Appendix 6.2. The Expressions for the Posterior Densities; Appendix 6.3. The Derivation of Computational Algorithms; Appendix 6.4. Evaluation of the Cramér-Rao Lower Bound in Multi- variate AR Systems; Problems
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|a CHAPTER VII. PARAMETER ESTIMATION IN SYSTEMS WITH BOTH MOVING AVERAGE AND AUTOREGRESSIVE TERMSIntroduction; 7a. Maximum Likelihood Estimators; 7b. Numerical Methods for CML Estimation; 7c. Limited Information Estimates; 7d. Numerical Experiments with Estimation Methods; 7e. Conclusions; Problems; CHAPTER VIII. CLASS SELECTION AND VALIDATION OF UNIVARIATE MODELS; Introduction; 8a. The Nature of the Selection Problem; 8b. The Different Methods of Class Selection; 8c. Validation of Fitted Models; 8d. Discussion of Selection and Validation; 8e. Conclusions
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|a Dynamic stochastic models from empirical data.
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590 |
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|a eBooks on EBSCOhost
|b EBSCO eBook Subscription Academic Collection - Worldwide
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650 |
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|a Time-series analysis.
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650 |
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|a Stochastic processes.
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|a Estimation theory.
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|a System analysis.
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2 |
|a Stochastic Processes
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|a Systems Analysis
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|a Série chronologique.
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|a Processus stochastiques.
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|a Théorie de l'estimation.
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|a Analyse de systèmes.
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|a systems analysis.
|2 aat
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|a MATHEMATICS
|x Probability & Statistics
|x General.
|2 bisacsh
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650 |
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7 |
|a Estimation theory
|2 fast
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650 |
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7 |
|a Stochastic processes
|2 fast
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|a System analysis
|2 fast
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|a Time-series analysis
|2 fast
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650 |
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|a Processus stochastiques.
|2 ram
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|a Systèmes, Analyse de.
|2 ram
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|a Séries chronologiques.
|2 ram
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700 |
1 |
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|a Rao, A. Ramachandra
|q (Adiseshappa Ramachandra),
|d 1939-
|
776 |
0 |
8 |
|i Print version:
|a Kashyap, Rangasami L. (Rangasami Laksminarayana), 1938-
|t Dynamic stochastic models from empirical data.
|d New York : Academic Press, 1976
|z 9780124005501
|w (DLC) 75013093
|w (OCoLC)1975888
|
830 |
|
0 |
|a Mathematics in science and engineering ;
|v v. 122.
|
856 |
4 |
0 |
|u https://ebsco.uam.elogim.com/login.aspx?direct=true&scope=site&db=nlebk&AN=297096
|z Texto completo
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938 |
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|a ProQuest Ebook Central
|b EBLB
|n EBL453034
|
938 |
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|a ebrary
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|
938 |
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|a EBSCOhost
|b EBSC
|n 297096
|
938 |
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|a Internet Archive
|b INAR
|n dynamicstochasti0122kash
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994 |
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|a 92
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|