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Statistical decision problems selected von zabarankin michael (5 Ergebnisse)

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  • Sprache: Englisch

    Verlag: Springer Verlag, 2016

    1493953257 / 9781493953257

    Serie: Buch 78 von 176 - Springer Optimization and Its Applications

    • Softcover

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    Paperback. Zustand: Brand New. reprint edition. 263 pages. 9.25x6.25x0.75 inches. In Stock.

  • Sprache: Englisch

    Verlag: Springer Verlag, 2014

    1461484707 / 9781461484707

    Serie: Buch 78 von 176 - Springer Optimization and Its Applications

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    Hardcover. Zustand: Brand New. 249 pages. 9.25x6.25x0.75 inches. In Stock.

  • Sprache: Englisch

    Verlag: Springer US, 2013

    1461484707 / 9781461484707

    Serie: Buch 78 von 176 - Springer Optimization and Its Applications

    • Hardcover

    Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH

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    Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Statistical Decision Problems presents a quick and concise introduction into the theory of risk, deviation and error measures that play a key role in statistical decision problems. It introduces state-of-the-art practical decision making through twenty-one case studies from real-life applications. The case studies cover a broad area of topics and the authors include links with source code and data, a very helpful tool for the reader. In its core, the text demonstrates how to use different factors to formulate statistical decision problems arising in various risk management applications, such as optimal hedging, portfolio optimization, cash flow matching, classification, and more. The presentation is organized into three parts: selected concepts of statistical decision theory, statistical decision problems, and case studies with portfolio safeguard. The text is primarily aimed at practitioners in the areas of risk management, decision making, and statistics. However, the inclusion of a fair bit of mathematical rigor renders this monograph an excellent introduction to the theory of general error, deviation, and risk measures for graduate students. It can be used as supplementary reading for graduate courses including statistical analysis, data mining, stochastic programming, financial engineering, to name a few. The high level of detail may serve useful to applied mathematicians, engineers, and statisticians interested in modeling and managing risk in various applications.…

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    Sprache: Englisch

    Verlag: Springer, 2016

    1493953257 / 9781493953257

    Serie: Buch 78 von 176 - Springer Optimization and Its Applications

    • Softcover

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    Taschenbuch. Zustand: Neu. Statistical Decision Problems | Selected Concepts and Portfolio Safeguard Case Studies | Michael Zabarankin (u. a.) | Taschenbuch | Springer Optimization and Its Applications | xiv | Englisch | 2016 | Springer | EAN 9781493953257 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

  • Sprache: Englisch

    Verlag: Springer New York, 2013

    1461484707 / 9781461484707

    Serie: Buch 78 von 176 - Springer Optimization and Its Applications

    • Hardcover

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    Aktueller Preis: EUR 40,67

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    Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 264 | Sprache: Englisch | Produktart: Bücher | Statistical Decision Problems presents a quick and concise introduction into the theory of risk, deviation and error measures that play a key role in statistical decision problems. It introduces state-of-the-art practical decision making through twenty-one case studies from real-life applications. The case studies cover a broad area of topics and the authors include links with source code and data, a very helpful tool for the reader. In its core, the text demonstrates how to use different factors to formulate statistical decision problems arising in various risk management applications, such as optimal hedging, portfolio optimization, cash flow matching, classification, and more.   The presentation is organized into three parts: selected concepts of statistical decision theory, statistical decision problems, and case studies with portfolio safeguard. The text is primarily aimed at practitioners in the areas of risk management, decision making, and statistics. However, the inclusion of a fair bit of mathematical rigor renders this monograph an excellent introduction to the theory of general error, deviation, and risk measures for graduate students. It can be used as supplementary reading for graduate courses including statistical analysis, data mining, stochastic programming, financial engineering, to name a few. The high level of detail may serve useful to applied mathematicians, engineers, and statisticians interested in modeling and managing risk in various applications.…