Optimization Heuristics in Econometrics : Applications of Threshold AcceptingISBN: 978-0-471-85631-3
Hardcover
360 pages
December 2000
This is a Print-on-Demand title. It will be printed specifically to fill your order. Please allow an additional 10-15 days delivery time. The book is not returnable.
|
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.
* 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.