Optimization Techniques In Statistics
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Introduction To Optimization Methods And Their Application In Statistics
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Author : B. Everitt
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Introduction To Optimization Methods And Their Application In Statistics written by B. Everitt and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Social Science categories.
Optimization techniques are used to find the values of a set of parameters which maximize or minimize some objective function of interest. Such methods have become of great importance in statistics for estimation, model fitting, etc. This text attempts to give a brief introduction to optimization methods and their use in several important areas of statistics. It does not pretend to provide either a complete treatment of optimization techniques or a comprehensive review of their application in statistics; such a review would, of course, require a volume several orders of magnitude larger than this since almost every issue of every statistics journal contains one or other paper which involves the application of an optimization method. It is hoped that the text will be useful to students on applied statistics courses and to researchers needing to use optimization techniques in a statistical context. Lastly, my thanks are due to Bertha Lakey for typing the manuscript.
Optimization Techniques In Statistics
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Author : Jagdish S. Rustagi
language : en
Publisher: Elsevier
Release Date : 2014-05-19
Optimization Techniques In Statistics written by Jagdish S. Rustagi and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-19 with Mathematics categories.
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 estimates, Markov decision processes, Programming methods used to optimize monitoring of patients in hospitals, Derivation of the Neyman-Pearson lemma, The search for optimal designs, Simulation of a steel mill. Suitable 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. - Covers optimization from traditional methods to recent developments such as Karmarkars algorithm and simulated annealing - Develops a wide range of statistical techniques in the unified context of optimization - Discusses applications such as optimizing monitoring of patients and simulating steel mill operations - Treats numerical methods and applications - Includes exercises and references for each chapter - Covers topics such as linear, nonlinear, and dynamic programming, variational methods, and stochastic optimization
Optimization Techniques In Statistics
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Author : Rustagi
language : en
Publisher:
Release Date : 1992-06-01
Optimization Techniques In Statistics written by Rustagi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992-06-01 with categories.
Db2 Optimization Techniques For Sap Database Migration To The Cloud
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Author : Dino Quintero
language : en
Publisher: IBM Redbooks
Release Date : 2024-04-02
Db2 Optimization Techniques For Sap Database Migration To The Cloud written by Dino Quintero and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-02 with Computers categories.
For many years, SAP migrations have been a standard process. An increasing number of customers are changing their database software to IBM® Db2® for UNIX, Linux, and Windows or are moving their existing Db2 based infrastructure from on-premises into the cloud. When customers move to the cloud, a heterogeneous system copy is often needed because of a change in the underlying hardware architecture and operating system. This book provides in-depth information about the best practices and recommendations for the source system database export, the advanced migration techniques, database layout and configuration, database import recommendations, SAP NetWeaver Business Warehouse, in addition to background information about Unicode. The book includes best practices in a single chapter that can be used as a quick reference for experienced migration consultants. It describes optimization strategies and best practices for migrating SAP systems to IBM Db2 for Linux, UNIX, and Windows. It is intended for experienced SAP migration experts and discusses IBM Db2 specific recommendations and best practices. It addresses advanced SAP migration techniques, considerations for database layout and tuning, and presents unique Db2 capabilities. All techniques discussed within this book are based on extensive tests and experiences collected from countless migration projects. However, it is important to understand that some advanced optimizations described in this document might introduce risks to the overall process because of their complexity. Other optimizations might require changes to the production system. Therefore, use these features during migration only when the downtime window might not be large enough. The authors want this book to be as helpful as possible. If you want to provide feedback on the recommendations or if you have suggestions or questions, you are welcome to contact the authors.
Computational Intelligence For Missing Data Imputation Estimation And Management Knowledge Optimization Techniques
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Author : Marwala, Tshilidzi
language : en
Publisher: IGI Global
Release Date : 2009-04-30
Computational Intelligence For Missing Data Imputation Estimation And Management Knowledge Optimization Techniques written by Marwala, Tshilidzi and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-30 with Computers categories.
"This book is for those who use data analysis to build decision support systems, particularly engineers, scientists and statisticians"--Provided by publisher.
Process Optimization
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Author : Enrique del Castillo
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-09-14
Process Optimization written by Enrique del Castillo and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-09-14 with Mathematics categories.
PROCESS OPTIMIZATION: A Statistical Approach is a textbook for a course in experimental optimization techniques for industrial production processes and other "noisy" systems where the main emphasis is process optimization. The book can also be used as a reference text by Industrial, Quality and Process Engineers and Applied Statisticians working in industry, in particular, in semiconductor/electronics manufacturing and in biotech manufacturing industries.
Optimizing Methods In Statistics
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Author : Jagdish S. Rustagi
language : en
Publisher: Academic Press
Release Date : 2014-05-10
Optimizing Methods In Statistics written by Jagdish S. Rustagi and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-10 with Mathematics categories.
Optimizing Method in Statistics is a compendium of papers dealing with variational methods, regression analysis, mathematical programming, optimum seeking methods, stochastic control, optimum design of experiments, optimum spacings, and order statistics. One paper reviews three optimization problems encountered in parameter estimation, namely, 1) iterative procedures for maximum likelihood estimation, based on complete or censored samples, of the parameters of various populations; 2) optimum spacings of quantiles for linear estimation; and 3) optimum choice of order statistics for linear estimation. Another paper notes the possibility of posing various adaptive filter algorithms to make the filter learn the system model while the system is operating in real time. By reducing the time necessary for process modeling, the time required to implement the acceptable system design can also be reduced One paper evaluates the parallel structure between duality relationships for the linear functional version of the generalized Neyman-Pearson problem, as well as the duality relationships of linear programming as these apply to bounded-variable linear programming problems. The compendium can prove beneficial to mathematicians, students, and professor of calculus, statistics, or advanced mathematics.
Optimizing Methods In Statistics
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Author : Jagdish S. Rustagi
language : en
Publisher:
Release Date : 1971
Optimizing Methods In Statistics written by Jagdish S. Rustagi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1971 with Business & Economics categories.
Optimizing Methods in Statistics.
Optimization In Statistics
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Author : S. H. Zanakis
language : en
Publisher: North Holland
Release Date : 1982
Optimization In Statistics written by S. H. Zanakis and has been published by North Holland this book supported file pdf, txt, epub, kindle and other format this book has been release on 1982 with Mathematics categories.
Introduction To Optimization Methods And Their Application In Statistics
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Author : B. Everitt
language : en
Publisher: Springer
Release Date : 1987-10
Introduction To Optimization Methods And Their Application In Statistics written by B. Everitt and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 1987-10 with Juvenile Nonfiction categories.
Optimization techniques are used to find the values of a set of parameters which maximize or minimize some objective function of interest. Such methods have become of great importance in statistics for estimation, model fitting, etc. This text attempts to give a brief introduction to optimization methods and their use in several important areas of statistics. It does not pretend to provide either a complete treatment of optimization techniques or a comprehensive review of their application in statistics; such a review would, of course, require a volume several orders of magnitude larger than this since almost every issue of every statistics journal contains one or other paper which involves the application of an optimization method. It is hoped that the text will be useful to students on applied statistics courses and to researchers needing to use optimization techniques in a statistical context. Lastly, my thanks are due to Bertha Lakey for typing the manuscript.