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  • Language: German

    Published by Springer, 2004

    354020380X / 9783540203803

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    Condition: good. Befriedigend/Good: Durchschnittlich erhaltenes Buch bzw. Schutzumschlag mit Gebrauchsspuren, aber vollständigen Seiten. / Describes the average WORN book or dust jacket that has all the pages present.

  • Language: German

    Published by Springer, 2004

    354020380X / 9783540203803

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    Condition: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.

  • Language: English

    Published by Birkhäuser, 2002

    0817642013 / 9780817642013

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    Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

  • Language: English

    Published by Birkhäuser, 2002

    0817642013 / 9780817642013

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    hardcover. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.

  • Language: English

    Published by Birkhäuser, 2002

    0817642013 / 9780817642013

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    Condition: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

  • Language: German

    Published by Springer, 2004

    354020380X / 9783540203803

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  • Language: German

    Published by Springer 3/8/2004, 2004

    354020380X / 9783540203803

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    Paperback or Softback. Condition: New. Einf�hrung in Die Wahrscheinlichkeitstheorie Und Statistik. Book.

  • Language: German

    Published by Springer, Berlin, 2004

    354020380X / 9783540203803

    • Softcover

    Seller: Antiquariat Renner OHG, Albstadt, GermanyAntiquariat Renner OHG

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    Softcover. Condition: Sehr gut. 2. Aufl. Berlin, Springer (2004). gr.8°. Einige Abb. XIII, 306 S. OKart. Statistik und ihre Anwendungen.- Mit Aufgaben.- Sehr gut erhalten.

  • Language: English

    Published by Springer, 2002

    0817642013 / 9780817642013

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    Condition: Used. pp. 398.

  • Language: English

    Published by Elsevier Science, 2007

    0444520260 / 9780444520265

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  • Language: English

    Published by Springer, 2002

    0817642013 / 9780817642013

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    Condition: Used. pp. 398 68:B&W 7 x 10 in or 254 x 178 mm Case Laminate on White w/Gloss Lam.

  • Language: English

    Published by Birkh?user, 2012

    1461266114 / 9781461266112

    • Softcover

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    Condition: New. 2012. Paperback. . . . . .

  • Language: English

    Published by Springer, 2002

    0817642013 / 9780817642013

    • Hardcover

    Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios

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    Condition: Used. pp. 398.

  • Language: English

    Published by Elsevier Science, 2007

    0444520260 / 9780444520265

    • Hardcover

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  • Language: German

    Published by Springer, 2004

    354020380X / 9783540203803

    • Softcover

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  • Language: English

    Published by Elsevier Science and Technology, GB, 2007

    0444520260 / 9780444520265

    • Hardcover

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    Hardback. Condition: New. There is an ever increasing need for modelling complex processes reliably. Computational modelling techniques, such as CFD and MD may be used as tools to study specific systems, but their emergence has not decreased the need for generic, analytical process models. Multiphase and multicomponent systems, and high-intensity processes displaying a highly complex behaviour are becoming omnipresent in the processing industry. This book discusses an elegant, but little-known technique for formulating process models in process technology: stochastic process modelling. The technique is based on computing the probability distribution for a single particle's position in the process vessel, and/or the particle's properties, as a function of time, rather than - as is traditionally done - basing the model on the formulation and solution of differential conservation equations. Using this technique can greatly simplify the formulation of a model, and even make modelling possible for processes so complex that the traditional method is impracticable. Stochastic modelling has sporadically been used in various branches of process technology under various names and guises. This book gives, as the first, an overview of this work, and shows how these techniques are similar in nature, and make use of the same basic mathematical tools and techniques. The book also demonstrates how stochastic modelling may be implemented by describing example cases, and shows how a stochastic model may be formulated for a case, which cannot be described by formulating and solving differential balance equations. …

  • Language: English

    Published by Birkhäuser, 2012

    1461266114 / 9781461266112

    • Softcover

    Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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    Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Empirical process techniques for independent data have been used for many years in statistics and probability theory. These techniques have proved very useful for studying asymptotic properties of parametric as well as non-parametric statistical procedures. Recently, the need to model the dependence structure in data sets from many different subject areas such as finance, insurance, and telecommunications has led to new developments concerning the empirical distribution function and the empirical process for dependent, mostly stationary sequences. This work gives an introduction to this new theory of empirical process techniques, which has so far been scattered in the statistical and probabilistic literature, and surveys the most recent developments in various related fields. Key features: A thorough and comprehensive introduction to the existing theory of empirical process techniques for dependent data \* Accessible surveys by leading experts of the most recent developments in various related fields \* Examines empirical process techniques for dependent data, useful for studying parametric and non-parametric statistical procedures \* Comprehensive bibliographies \* An overview of applications in various fields related to empirical processes: e.g., spectral analysis of time-series, the bootstrap for stationary sequences, extreme value theory, and the empirical process for mixing dependent observations, including the case of strong dependence. To date this book is the only comprehensive treatment of the topic in book literature. It is an ideal introductory text that will serve as a reference or resource for classroom use in the areas of statistics, time-series analysis, extreme value theory, point process theory, and applied probability theory. Contributors: P. Ango Nze, M.A. Arcones, I. Berkes, R. Dahlhaus, J. Dedecker, H.G. Dehling.…

  • Language: English

    Published by Springer, 2012

    1461266114 / 9781461266112

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    Condition: New. pp. 398.

  • Language: English

    Published by Amsterdam, Elsevier, 2007

    0444520260 / 9780444520265

    • Hardcover

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    Hardcover. Condition: Gut. Ex-library with stamp and library-signature. GOOD condition, some traces of use. Ancien Exemplaire de bibliothèque avec signature et cachet. BON état, quelques traces d'usure. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. 60 DEH 9780444520265 Sprache: Englisch Gewicht in Gramm: 1150.…

  • Language: English

    Published by Birkh?user, 2012

    1461266114 / 9781461266112

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    Condition: New. 2012. Paperback. . . . . . Books ship from the US and Ireland.

  • Language: English

    Published by Elsevier Science, 2007

    0444520260 / 9780444520265

    • Hardcover

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    Gebunden. Condition: New. Introduction to stochastic process modelling as an alternative modelling technique Shows how stochastic modelling may be succesful where the traditional technique fails Overview of stochastic modelling in process technology in the.

  • Language: English

    Published by Birkh?user, 2002

    0817642013 / 9780817642013

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    Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrelandKennys Bookshop and Art Galleries Ltd.

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    Condition: New. 2002. Hardcover. . . . . .

  • Language: English

    Published by Elsevier, 2007

    0444520260 / 9780444520265

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    Condition: New. pp. 292.

  • Language: English

    Published by Elsevier Science, 2007

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  • Language: English

    Published by Elsevier Science, 2007

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  • Language: English

    Published by Elsevier, 2007

    0444520260 / 9780444520265

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    Condition: New. pp. 292 Illus.

  • Language: English

    Published by Elsevier Science, 2007

    0444520260 / 9780444520265

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  • Language: English

    Published by SPRINGER, 2002

    0817642013 / 9780817642013

    • Hardcover
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    Seller: UK BOOKS STORE, London, LONDO, United KingdomUK BOOKS STORE

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    Condition: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.…

  • Language: English

    Published by Elsevier Science and Technology, GB, 2007

    0444520260 / 9780444520265

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    Hardback. Condition: New. There is an ever increasing need for modelling complex processes reliably. Computational modelling techniques, such as CFD and MD may be used as tools to study specific systems, but their emergence has not decreased the need for generic, analytical process models. Multiphase and multicomponent systems, and high-intensity processes displaying a highly complex behaviour are becoming omnipresent in the processing industry. This book discusses an elegant, but little-known technique for formulating process models in process technology: stochastic process modelling. The technique is based on computing the probability distribution for a single particle's position in the process vessel, and/or the particle's properties, as a function of time, rather than - as is traditionally done - basing the model on the formulation and solution of differential conservation equations. Using this technique can greatly simplify the formulation of a model, and even make modelling possible for processes so complex that the traditional method is impracticable. Stochastic modelling has sporadically been used in various branches of process technology under various names and guises. This book gives, as the first, an overview of this work, and shows how these techniques are similar in nature, and make use of the same basic mathematical tools and techniques. The book also demonstrates how stochastic modelling may be implemented by describing example cases, and shows how a stochastic model may be formulated for a case, which cannot be described by formulating and solving differential balance equations. …

  • Language: English

    Published by Birkhäuser, 2012

    1461266114 / 9781461266112

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    Paperback. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.