Optimization Techniques in Statistics - Couverture rigide

Livre 10 sur 12: Statistical Modeling and Decision Science

Rustagi, Jagdish S.

 
9780126045550: Optimization Techniques in Statistics
Couverture rigide
ISBN 10 : 0126045550 ISBN 13 : 9780126045550
Editeur : Academic Press Inc, 1994

Synopsis

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. The text features numerous applications, including:Finding maximum likelihood estimatesMarkov decision processesProgramming methods used to optimize monitoring of patients in hospitalsDerivation of the Neyman-Pearson lemmaThe search for optimal designsSimulation of a steel millSuitable as both a reference and a text, this book will be of interest to advanced undergraduate or beginning graduate students in statistics, operations research, management and engineering sciences, and related fields. Most of the material can be covered in one semester by students with a basic background in probability and statistics.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

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. The text features numerous applications, including: Finding maximum likelihood estimatesMarkov decision processesProgramming methods used to optimize monitoring of patients in hospitalsDerivation of the Neyman-Pearson lemmaThe search for optimal designsSimulation of a steel millSuitable as both a reference and a text, this book will be of interest to advanced undergraduate or beginning graduate students in statistics, operations research, management and engineering sciences, and related fields. Most of the material can be covered in one semester by students with a basic background in probability and statistics.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
Academic Press Inc
Date d'édition
1994
Langue
anglais
ISBN 10 
0126045550
ISBN 13 
9780126045550
Reliure
Relié
Nombre de pages
359
Coordonnées du fabricant
non disponible
Personne responsable
Yeepin GmbH
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67655
Allemagne

Autres éditions populaires du même titre

9781493307425: Optimization Techniques in Statistics

Edition présentée

ISBN 10 :  1493307428 ISBN 13 :  9781493307425
Editeur : Academic Press, 2014
Couverture souple