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Optimization Heuristics in Econometrics

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Hardback
10-November-2000
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Many problems in statistics and econometrics offer themselves naturally to the use of optimization heuristics. Standard methods applied to highly complex problems often produce approximate results, of unknown quality, based on heavy assumptions. Optimization heuristic methods provide powerful results to many complex problems, combined with relatively simple implementation. The techniques used in optimization heurisitics can be applied to problems encountered in econometrics, statistics and operations research.
* Offers a self-contained introduction to optimization heuristics in econometrics and statistics
* Features many examples of optimization heuristic methods applied to real problems
* Includes detailed coverage of the threshold accepting heuristic methods applied to real problems
* Provides suggestions for further reading
Split into three parts, the book opens with a general introduction to optimization in statistics and econometrics, followed by detailed discussion of a relatively new and very powerful optimization heuristic, threshold accepting. The final part consists of many applications of the methods described earlier, encompassing experimental design, model selection, aggregation of time series, and censored quantile regression models.
Those researching and working in econometrics, statistics and operations research are given the tools to apply optimization heuristic methods to real problems in their work. Postgraduate students of statistics and econometrics will find the book provides a good introduction to optimization heuristic methods.

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    Product Details
    ISBN-13
    9780471856313
    Author
    Peter Winker
    Publisher
    John Wiley & Sons (UK)
    Published
    10-November-2000
    Format
    Hardback

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    $383.10
    Ships in 3-5 business days

    Delivery estimate

    Hurry up! Current stock:

    Optimization Heuristics in Econometrics

    $383.10

    Description

    Many problems in statistics and econometrics offer themselves naturally to the use of optimization heuristics. Standard methods applied to highly complex problems often produce approximate results, of unknown quality, based on heavy assumptions. Optimization heuristic methods provide powerful results to many complex problems, combined with relatively simple implementation. The techniques used in optimization heurisitics can be applied to problems encountered in econometrics, statistics and operations research.
    * Offers a self-contained introduction to optimization heuristics in econometrics and statistics
    * Features many examples of optimization heuristic methods applied to real problems
    * Includes detailed coverage of the threshold accepting heuristic methods applied to real problems
    * Provides suggestions for further reading
    Split into three parts, the book opens with a general introduction to optimization in statistics and econometrics, followed by detailed discussion of a relatively new and very powerful optimization heuristic, threshold accepting. The final part consists of many applications of the methods described earlier, encompassing experimental design, model selection, aggregation of time series, and censored quantile regression models.
    Those researching and working in econometrics, statistics and operations research are given the tools to apply optimization heuristic methods to real problems in their work. Postgraduate students of statistics and econometrics will find the book provides a good introduction to optimization heuristic methods.

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