Time series research has been an area of considerable research activity over the past several decades. The essential ingredient --- the notion of time-dependence --- is required for measuring and then accurately predicting data to construct suitable models for diverse phenomena. This fairly self-contained volume, written by leading experts in their respective fields, especially focuses on the theoretical concepts, methodologies, and practical applications pertaining to self-similar processes and long-range dependent phenomena. Graduate students, researchers, and professionals in industry will benefit from the book.
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Vendeur : killarneybooks, Inagh, CLARE, Irlande
Hardcover. Etat : Good. Oversized & heavy hardcover, x + 719 pages. Stamped "withdrawn". A thick black marker line on upper page edges externally; a couple of blank stickers inside the front board; neatly removed title page. Else book shows little wear, interior is clean and bright with unmarked text, firmly bound. Issued without a dust jacket. -- Contents: Preface; Part A: Theory I. Probability -- Fractional Brownian Motion and Long-Range Dependence; Historical Comments Related to Fractional Brownian Motion; Models, Inequalities and Limit Theorems for Stationary Sequences; Limit Theorems Under Seasonal Long-Memory; CLTs for Polynomials of Linear Sequences: Diagram Formula with Illustrations; Non-CLTs: U-Statistics, Multinomial Formula and Approximations of Multiple Ito-Wiener Integrals; A Decomposition for Generalized U-Statistics of Long-Memory Linear Processes; Limit Theorems for Infinite Variance Sequences; Fractional Calculus and Its Connection to Fractional Brownian Motion; Stochastic Integration, Filtering with Respect to Fractional Brownian Motion; II. Statistics -- Parametric Estimation Under Long-Range Dependence; Semiparametric Spectral Estimation for Fractional Processes; Nonparametric Estimation for Long-Range Dependent Sequences; Estimation of Long Memory in Volatility; Detection and Estimation of Changes in Regime; Robust Estimators in Regression Models with Long Memory Errors; Prediction of Long-Memory Time Series; Part B: Applications III. Applications -- Long-Range Dependence and Data Network Traffic; Large Deviations of Queues with Long-Range Dependent Input; Long-Range Dependence Paradigm for Macroeconomics and Finance; Long-Range Dependence Effects and ARCH Modeling; Long-Range Dependence in Hydrology; Wavelet Based Estimation of Local Kolmogorov Turbulence; Limit Theorems for the Burgers Equation Initialized by Data with Long-Range Dependence; IV. Methodology -- Self-Similarity and Long-Range Dependence Through the Wavelet Lens; Semi-Parametric Estimation of the Long-Range Dependence Parameter: A Survey; Generators of Long-Range Dependent Processes: A Survey; Multifractal Processes -- The area of data analysis has been greatly affected by our computer age. For example, the issue of collecting and storing huge data sets has become quite simplified and has greatly affected such areas as finance and telecommunications. Even non-specialists try to analyze data sets and ask basic questions about their structure. One such question is whether one observes some type of invariance with respect to scale, a question that is closely related to the existence of long-range dependence in the data. This important topic of long-range dependence is the focus of this unique work, written by a number of specialists on the subject. The topics selected should give a good overview from the probabilistic and statistical perspective. Included will be articles on fractional Brownian motion, models, inequalities and limit theorems, periodic long-range dependence, parametric, semiparametric, and non-parametric estimation, long-memory stochastic volatility models, robust estimation, and prediction for long-range dependence sequences. For those graduate students and researchers who want to use the methodology and need to know the "tricks of the trade," there will be a special section called "Mathematical Techniques." Topics in the first part of the book are covered from probabilistic and statistical perspectives and include fractional Brownian motion, models, inequalities and limit theorems, periodic long-range dependence, parametric, semiparametric, and non-parametric estimation, long-memory stochastic volatility models, robust estimation, prediction for long-range dependence sequences. The reader is referred to more detailed proofs if already found in the literature. N° de réf. du vendeur 007214
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Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Etat : New. In. N° de réf. du vendeur ria9780817641689_new
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Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Etat : New. N° de réf. du vendeur 206826-n
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Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : New. N° de réf. du vendeur 206826-n
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Vendeur : moluna, Greven, Allemagne
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The area of data analysis has been greatly affected by our computer age. For example, the issue of collecting and storing huge data sets has become quite simplified and has greatly affected such areas as finance and telecommunications. Even non-specialis. N° de réf. du vendeur 5975689
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Vendeur : Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlande
Etat : New. 2002. Hardcover. . . . . . N° de réf. du vendeur V9780817641689
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Vendeur : Books Puddle, New York, NY, Etats-Unis
Etat : New. pp. 736. N° de réf. du vendeur 26321442
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Vendeur : Majestic Books, Hounslow, Royaume-Uni
Etat : New. Print on Demand pp. 736 68:B&W 7 x 10 in or 254 x 178 mm Case Laminate on White w/Gloss Lam. N° de réf. du vendeur 7559293
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Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
Etat : New. PRINT ON DEMAND pp. 736. N° de réf. du vendeur 18321448
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Vendeur : Kennys Bookstore, Olney, MD, Etats-Unis
Etat : New. 2002. Hardcover. . . . . . Books ship from the US and Ireland. N° de réf. du vendeur V9780817641689
Quantité disponible : 15 disponible(s)