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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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Lenguaje: | eng |
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Academic Press
1994
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Acceso en línea: | http://cds.cern.ch/record/1985903 |
_version_ | 1780945412842061824 |
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author | Rustagi, Jagdish S |
author_facet | Rustagi, Jagdish S |
author_sort | Rustagi, Jagdish S |
collection | CERN |
description | 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 optimiza |
id | cern-1985903 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 1994 |
publisher | Academic Press |
record_format | invenio |
spelling | cern-19859032021-04-21T20:36:36Zhttp://cds.cern.ch/record/1985903engRustagi, Jagdish SOptimization techniques in statisticsMathematical Physics and MathematicsStatistics 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 optimizaAcademic Pressoai:cds.cern.ch:19859031994 |
spellingShingle | Mathematical Physics and Mathematics Rustagi, Jagdish S Optimization techniques in statistics |
title | Optimization techniques in statistics |
title_full | Optimization techniques in statistics |
title_fullStr | Optimization techniques in statistics |
title_full_unstemmed | Optimization techniques in statistics |
title_short | Optimization techniques in statistics |
title_sort | optimization techniques in statistics |
topic | Mathematical Physics and Mathematics |
url | http://cds.cern.ch/record/1985903 |
work_keys_str_mv | AT rustagijagdishs optimizationtechniquesinstatistics |