Optimization techniques in statistics /
Statistics help guide us to optimal decisions under uncertainty. A large variety of statistical problems are essentially solutions to optimization problems. The mathematical techniques of optimization are fundamentalto statistical theory and practice. In this book, Jagdish Rustagi provides full-spec...
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| Format: | eBook |
| Language: | English |
| Language Notes: | English. |
| Published: |
Boston :
Academic Press,
©1994.
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| Series: | Statistical modeling and decision science.
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| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| Summary: | Statistics help guide us to optimal decisions under uncertainty. A large variety of statistical problems are essentially solutions to optimization problems. The mathematical techniques of optimization are fundamentalto statistical theory and practice. In this book, Jagdish Rustagi provides full-spectrum coverage of these methods, ranging from classical optimization and Lagrange multipliers, to numerical techniques using gradients or direct search, to linear, nonlinear, and dynamic programming using the Kuhn-Tucker conditions or the Pontryagin maximal principle. Variational methods and optimization in function spaces are also discussed, as are stochastic optimization in simulation, including annealing methods. |
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| Physical Description: | 1 online resource (xii, 359 pages) : illustrations |
| Format: | Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002. |
| Bibliography: | Includes bibliographical references (pages 325-341) and indexes. |
| ISBN: | 0126045550 9780126045550 9781483295718 1483295710 |