Optimization Methods For Applications In Statistics

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Optimization Techniques in Statistics

Author : Jagdish S. Rustagi
Publisher : Elsevier
ISBN 13 : 1483295710
Total Pages : 376 pages
Book Rating : 4.4/5 (832 download)

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Book Synopsis Optimization Techniques in Statistics by : Jagdish S. Rustagi

Download or read book Optimization Techniques in Statistics written by Jagdish S. Rustagi and published by Elsevier. This book was released on 2014-05-19 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Introduction to Optimization Methods and their Application in Statistics

Author : B. Everitt
Publisher : Springer Science & Business Media
ISBN 13 : 9400931530
Total Pages : 87 pages
Book Rating : 4.4/5 (9 download)

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Book Synopsis Introduction to Optimization Methods and their Application in Statistics by : B. Everitt

Download or read book Introduction to Optimization Methods and their Application in Statistics written by B. Everitt and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 87 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Methods for Applications in Statistics

Author : James E. Gentle
Publisher :
ISBN 13 : 9780387403168
Total Pages : 400 pages
Book Rating : 4.4/5 (31 download)

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Book Synopsis Optimization Methods for Applications in Statistics by : James E. Gentle

Download or read book Optimization Methods for Applications in Statistics written by James E. Gentle and published by . This book was released on 2006-01 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: No further information has been provided for this title.

Optimization Methods with Applications in Statistics

Author : Lutz Dümbgen
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (99 download)

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Book Synopsis Optimization Methods with Applications in Statistics by : Lutz Dümbgen

Download or read book Optimization Methods with Applications in Statistics written by Lutz Dümbgen and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Optimization Techniques and Applications with Examples

Author : Xin-She Yang
Publisher : John Wiley & Sons
ISBN 13 : 1119490545
Total Pages : 384 pages
Book Rating : 4.1/5 (194 download)

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Book Synopsis Optimization Techniques and Applications with Examples by : Xin-She Yang

Download or read book Optimization Techniques and Applications with Examples written by Xin-She Yang and published by John Wiley & Sons. This book was released on 2018-09-19 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide to modern optimization applications and techniques in newly emerging areas spanning optimization, data science, machine intelligence, engineering, and computer sciences Optimization Techniques and Applications with Examples introduces the fundamentals of all the commonly used techniques in optimization that encompass the broadness and diversity of the methods (traditional and new) and algorithms. The author—a noted expert in the field—covers a wide range of topics including mathematical foundations, optimization formulation, optimality conditions, algorithmic complexity, linear programming, convex optimization, and integer programming. In addition, the book discusses artificial neural network, clustering and classifications, constraint-handling, queueing theory, support vector machine and multi-objective optimization, evolutionary computation, nature-inspired algorithms and many other topics. Designed as a practical resource, all topics are explained in detail with step-by-step examples to show how each method works. The book’s exercises test the acquired knowledge that can be potentially applied to real problem solving. By taking an informal approach to the subject, the author helps readers to rapidly acquire the basic knowledge in optimization, operational research, and applied data mining. This important resource: Offers an accessible and state-of-the-art introduction to the main optimization techniques Contains both traditional optimization techniques and the most current algorithms and swarm intelligence-based techniques Presents a balance of theory, algorithms, and implementation Includes more than 100 worked examples with step-by-step explanations Written for upper undergraduates and graduates in a standard course on optimization, operations research and data mining, Optimization Techniques and Applications with Examples is a highly accessible guide to understanding the fundamentals of all the commonly used techniques in optimization.

Optimization Methods, Theory and Applications

Author : Honglei Xu
Publisher : Springer
ISBN 13 : 3662470446
Total Pages : 212 pages
Book Rating : 4.6/5 (624 download)

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Book Synopsis Optimization Methods, Theory and Applications by : Honglei Xu

Download or read book Optimization Methods, Theory and Applications written by Honglei Xu and published by Springer. This book was released on 2015-06-17 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the latest research findings and state-of-the-art solutions on optimization techniques and provides new research direction and developments. Both the theoretical and practical aspects of the book will be much beneficial to experts and students in optimization and operation research community. It selects high quality papers from The International Conference on Optimization: Techniques and Applications (ICOTA2013). The conference is an official conference series of POP (The Pacific Optimization Research Activity Group; there are over 500 active members). These state-of-the-art works in this book authored by recognized experts will make contributions to the development of optimization with its applications.

Optimization Methods and Applications

Author : Sergiy Butenko
Publisher : Springer
ISBN 13 : 3319686402
Total Pages : 637 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Optimization Methods and Applications by : Sergiy Butenko

Download or read book Optimization Methods and Applications written by Sergiy Butenko and published by Springer. This book was released on 2018-02-20 with total page 637 pages. Available in PDF, EPUB and Kindle. Book excerpt: Researchers and practitioners in computer science, optimization, operations research and mathematics will find this book useful as it illustrates optimization models and solution methods in discrete, non-differentiable, stochastic, and nonlinear optimization. Contributions from experts in optimization are showcased in this book showcase a broad range of applications and topics detailed in this volume, including pattern and image recognition, computer vision, robust network design, and process control in nonlinear distributed systems. This book is dedicated to the 80th birthday of Ivan V. Sergienko, who is a member of the National Academy of Sciences (NAS) of Ukraine and the director of the V.M. Glushkov Institute of Cybernetics. His work has had a significant impact on several theoretical and applied aspects of discrete optimization, computational mathematics, systems analysis and mathematical modeling.

Optimization

Author : Kenneth Lange
Publisher : Springer Science & Business Media
ISBN 13 : 9780387203324
Total Pages : 282 pages
Book Rating : 4.2/5 (33 download)

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Book Synopsis Optimization by : Kenneth Lange

Download or read book Optimization written by Kenneth Lange and published by Springer Science & Business Media. This book was released on 2004-06-17 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lange is a Springer author of other successful books. This is the first book that emphasizes the applications of optimization to statistics. The emphasis on statistical applications will be especially appealing to graduate students of statistics and biostatistics.

Optimization Based Data Mining: Theory and Applications

Author : Yong Shi
Publisher : Springer Science & Business Media
ISBN 13 : 0857295047
Total Pages : 314 pages
Book Rating : 4.8/5 (572 download)

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Book Synopsis Optimization Based Data Mining: Theory and Applications by : Yong Shi

Download or read book Optimization Based Data Mining: Theory and Applications written by Yong Shi and published by Springer Science & Business Media. This book was released on 2011-05-16 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization techniques have been widely adopted to implement various data mining algorithms. In addition to well-known Support Vector Machines (SVMs) (which are based on quadratic programming), different versions of Multiple Criteria Programming (MCP) have been extensively used in data separations. Since optimization based data mining methods differ from statistics, decision tree induction, and neural networks, their theoretical inspiration has attracted many researchers who are interested in algorithm development of data mining. Optimization based Data Mining: Theory and Applications, mainly focuses on MCP and SVM especially their recent theoretical progress and real-life applications in various fields. These include finance, web services, bio-informatics and petroleum engineering, which has triggered the interest of practitioners who look for new methods to improve the results of data mining for knowledge discovery. Most of the material in this book is directly from the research and application activities that the authors’ research group has conducted over the last ten years. Aimed at practitioners and graduates who have a fundamental knowledge in data mining, it demonstrates the basic concepts and foundations on how to use optimization techniques to deal with data mining problems.

Optimization for Data Analysis

Author : Stephen J. Wright
Publisher : Cambridge University Press
ISBN 13 : 1316518981
Total Pages : 239 pages
Book Rating : 4.3/5 (165 download)

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Book Synopsis Optimization for Data Analysis by : Stephen J. Wright

Download or read book Optimization for Data Analysis written by Stephen J. Wright and published by Cambridge University Press. This book was released on 2022-04-21 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: A concise text that presents and analyzes the fundamental techniques and methods in optimization that are useful in data science.

Modern Optimization Techniques with Applications in Electric Power Systems

Author : Soliman Abdel-Hady Soliman
Publisher : Springer Science & Business Media
ISBN 13 : 146141752X
Total Pages : 430 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Modern Optimization Techniques with Applications in Electric Power Systems by : Soliman Abdel-Hady Soliman

Download or read book Modern Optimization Techniques with Applications in Electric Power Systems written by Soliman Abdel-Hady Soliman and published by Springer Science & Business Media. This book was released on 2011-12-15 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the application of some AI related optimization techniques in the operation and control of electric power systems. With practical applications and examples the use of functional analysis, simulated annealing, Tabu-search, Genetic algorithms and fuzzy systems for the optimization of power systems is discussed in detail. Preliminary mathematical concepts are presented before moving to more advanced material. Researchers and graduate students will benefit from this book. Engineers working in utility companies, operations and control, and resource management will also find this book useful.

Optimization and Control of Bilinear Systems

Author : Panos M. Pardalos
Publisher : Springer Science & Business Media
ISBN 13 : 0387736697
Total Pages : 388 pages
Book Rating : 4.3/5 (877 download)

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Book Synopsis Optimization and Control of Bilinear Systems by : Panos M. Pardalos

Download or read book Optimization and Control of Bilinear Systems written by Panos M. Pardalos and published by Springer Science & Business Media. This book was released on 2010-03-14 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covers developments in bilinear systems theory Focuses on the control of open physical processes functioning in a non-equilibrium mode Emphasis is on three primary disciplines: modern differential geometry, control of dynamical systems, and optimization theory Includes applications to the fields of quantum and molecular computing, control of physical processes, biophysics, superconducting magnetism, and physical information science

Optimization Algorithms

Author : Ozgur Baskan
Publisher : BoD – Books on Demand
ISBN 13 : 9535125923
Total Pages : 326 pages
Book Rating : 4.5/5 (351 download)

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Book Synopsis Optimization Algorithms by : Ozgur Baskan

Download or read book Optimization Algorithms written by Ozgur Baskan and published by BoD – Books on Demand. This book was released on 2016-09-21 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers state-of-the-art optimization methods and their applications in wide range especially for researchers and practitioners who wish to improve their knowledge in this field. It consists of 13 chapters divided into two parts: (I) Engineering applications, which presents some new applications of different methods, and (II) Applications in various areas, where recent contributions of state-of-the-art optimization methods to diverse fields are presented.

Statistical Inference via Convex Optimization

Author : Anatoli Juditsky
Publisher : Princeton University Press
ISBN 13 : 0691200319
Total Pages : 656 pages
Book Rating : 4.6/5 (912 download)

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Book Synopsis Statistical Inference via Convex Optimization by : Anatoli Juditsky

Download or read book Statistical Inference via Convex Optimization written by Anatoli Juditsky and published by Princeton University Press. This book was released on 2020-04-07 with total page 656 pages. Available in PDF, EPUB and Kindle. Book excerpt: This authoritative book draws on the latest research to explore the interplay of high-dimensional statistics with optimization. Through an accessible analysis of fundamental problems of hypothesis testing and signal recovery, Anatoli Juditsky and Arkadi Nemirovski show how convex optimization theory can be used to devise and analyze near-optimal statistical inferences. Statistical Inference via Convex Optimization is an essential resource for optimization specialists who are new to statistics and its applications, and for data scientists who want to improve their optimization methods. Juditsky and Nemirovski provide the first systematic treatment of the statistical techniques that have arisen from advances in the theory of optimization. They focus on four well-known statistical problems—sparse recovery, hypothesis testing, and recovery from indirect observations of both signals and functions of signals—demonstrating how they can be solved more efficiently as convex optimization problems. The emphasis throughout is on achieving the best possible statistical performance. The construction of inference routines and the quantification of their statistical performance are given by efficient computation rather than by analytical derivation typical of more conventional statistical approaches. In addition to being computation-friendly, the methods described in this book enable practitioners to handle numerous situations too difficult for closed analytical form analysis, such as composite hypothesis testing and signal recovery in inverse problems. Statistical Inference via Convex Optimization features exercises with solutions along with extensive appendixes, making it ideal for use as a graduate text.

Optimizing Methods in Statistics

Author : Jagdish S. Rustagi
Publisher :
ISBN 13 :
Total Pages : 514 pages
Book Rating : 4.:/5 (44 download)

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Book Synopsis Optimizing Methods in Statistics by : Jagdish S. Rustagi

Download or read book Optimizing Methods in Statistics written by Jagdish S. Rustagi and published by . This book was released on 1971 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimizing Methods in Statistics.

Optimization and Control with Applications

Author : Liqun Qi
Publisher : Springer Science & Business Media
ISBN 13 : 0387242554
Total Pages : 587 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Optimization and Control with Applications by : Liqun Qi

Download or read book Optimization and Control with Applications written by Liqun Qi and published by Springer Science & Business Media. This book was released on 2006-03-30 with total page 587 pages. Available in PDF, EPUB and Kindle. Book excerpt: A collection of 28 refereed papers grouped according to four broad topics: duality and optimality conditions, optimization algorithms, optimal control, and variational inequality and equilibrium problems. Suitable for researchers, practitioners and postgrads.

Practical Optimization Methods

Author : M. Asghar Bhatti
Publisher : Springer Science & Business Media
ISBN 13 : 1461205018
Total Pages : 711 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Practical Optimization Methods by : M. Asghar Bhatti

Download or read book Practical Optimization Methods written by M. Asghar Bhatti and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 711 pages. Available in PDF, EPUB and Kindle. Book excerpt: This introductory textbook adopts a practical and intuitive approach, rather than emphasizing mathematical rigor. Computationally oriented books in this area generally present algorithms alone, and expect readers to perform computations by hand, and are often written in traditional computer languages, such as Basic, Fortran or Pascal. This book, on the other hand, is the first text to use Mathematica to develop a thorough understanding of optimization algorithms, fully exploiting Mathematica's symbolic, numerical and graphic capabilities.