Linear Programming With Statistical Applications
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Linear Programming With Statistical Applications
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Author : Vincent Anthony Sposito
language : en
Publisher:
Release Date : 1996
Linear Programming With Statistical Applications written by Vincent Anthony Sposito and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with categories.
Linear Programming With Statistical Applications
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Author : Vincent A. Sposito
language : en
Publisher: Wiley-Blackwell
Release Date : 1989
Linear Programming With Statistical Applications written by Vincent A. Sposito and has been published by Wiley-Blackwell this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989 with Mathematics categories.
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
Linear And Nonlinear Optimization Using Spreadsheets Examples For Prescriptive Predictive And Descriptive Analytics
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Author : Michael J Brusco
language : en
Publisher: World Scientific
Release Date : 2024-10-08
Linear And Nonlinear Optimization Using Spreadsheets Examples For Prescriptive Predictive And Descriptive Analytics written by Michael J Brusco and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-08 with Business & Economics categories.
The use of spreadsheets to obtain solutions to a diverse array of examples offers a reader-friendly way of addressing a topic (optimization) that can sometimes be viewed as intimidating. Many people are readily familiar with spreadsheets and how they work, yet are apt to be unaware of the incredible power of Excel for solving some rather complex optimization problems. A major goal of the book is to sell readers on why it is so important to understand optimization, and a large collection of examples for a wide range of business decision making areas (e.g., production planning and scheduling, workforce planning and scheduling, location and supply chain distribution, location of emergency services, assembly line balancing, vehicle routing, project scheduling, revenue management, advertising, product design, payout schedules, productivity measurement, investment portfolio management, sports league scheduling, ranking models, etc.) affords a practical mechanism for achieving that goal. Another important contribution of the book is that it provides coverage of the mechanics of some common yet sophisticated statistical methods (regression, logistic regression, discriminant analysis, factor analysis, and cluster analysis), which are often opaque to many users of such methods.
University Of Michigan Official Publication
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Author :
language : en
Publisher: UM Libraries
Release Date : 1964
University Of Michigan Official Publication written by and has been published by UM Libraries this book supported file pdf, txt, epub, kindle and other format this book has been release on 1964 with Education, Higher categories.
Advances In Theoretical And Applied Statistics
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Author : Nicola Torelli
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-26
Advances In Theoretical And Applied Statistics written by Nicola Torelli 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 2013-06-26 with Mathematics categories.
This volume includes contributions selected after a double blind review process and presented as a preliminary version at the 45th Meeting of the Italian Statistical Society. The papers provide significant and innovative original contributions and cover a broad range of topics including: statistical theory; methods for time series and spatial data; statistical modeling and data analysis; survey methodology and official statistics; analysis of social, demographic and health data; and economic statistics and econometrics.
Computational Statistics
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Author : James E. Gentle
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-07-28
Computational Statistics written by James E. Gentle 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 2009-07-28 with Mathematics categories.
Computational inference is based on an approach to statistical methods that uses modern computational power to simulate distributional properties of estimators and test statistics. This book describes computationally intensive statistical methods in a unified presentation, emphasizing techniques, such as the PDF decomposition, that arise in a wide range of methods.
Computational Statistics
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Author :
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-04-29
Computational Statistics written by 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 2010-04-29 with Mathematics categories.
Computational inference is based on an approach to statistical methods that uses modern computational power to simulate distributional properties of estimators and test statistics. This book describes computationally intensive statistical methods in a unified presentation, emphasizing techniques, such as the PDF decomposition, that arise in a wide range of methods.
Nonlinear Parameter Optimization Using R Tools
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Author : John C. Nash
language : en
Publisher: John Wiley & Sons
Release Date : 2014-05-27
Nonlinear Parameter Optimization Using R Tools written by John C. Nash and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-27 with Mathematics categories.
Nonlinear Parameter Optimization Using R John C. Nash, Telfer School of Management, University of Ottawa, Canada A systematic and comprehensive treatment of optimization software using R In recent decades, optimization techniques have been streamlined by computational and artificial intelligence methods to analyze more variables, especially under non–linear, multivariable conditions, more quickly than ever before. Optimization is an important tool for decision science and for the analysis of physical systems used in engineering. Nonlinear Parameter Optimization with R explores the principal tools available in R for function minimization, optimization, and nonlinear parameter determination and features numerous examples throughout. Nonlinear Parameter Optimization with R: Provides a comprehensive treatment of optimization techniques Examines optimization problems that arise in statistics and how to solve them using R Enables researchers and practitioners to solve parameter determination problems Presents traditional methods as well as recent developments in R Is supported by an accompanying website featuring R code, examples and datasets Researchers and practitioners who have to solve parameter determination problems who are users of R but are novices in the field optimization or function minimization will benefit from this book. It will also be useful for scientists building and estimating nonlinear models in various fields such as hydrology, sports forecasting, ecology, chemical engineering, pharmaco-kinetics, agriculture, economics and statistics.
Solving Fully Neutrosophic Linear Programming Problem With Application To Stock Portfolio Selection
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Author : Hamiden Abd El-Wahed Khalifa
language : en
Publisher: Infinite Study
Release Date :
Solving Fully Neutrosophic Linear Programming Problem With Application To Stock Portfolio Selection written by Hamiden Abd El-Wahed Khalifa and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with Mathematics categories.
Neutrosophic set is considered as a generalized of crisp set, fuzzy set, and intuitionistic fuzzy set for representing the uncertainty, inconsistency, and incomplete knowledge about the real world problems. In this paper, a neutrosophic linear programming (NLP) problem with single-valued trapezoidal neutrosophic numbers is formulated and solved. A new method based on the so-called score function to find the neutrosophic optimal solution of fully neutrosophic linear programming (FNLP) problem is proposed.