Optimal Decision Statistics
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Optimal Decision Statistics
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Author : Pasquale De Marco
language : en
Publisher: Pasquale De Marco
Release Date : 2025-04-06
Optimal Decision Statistics written by Pasquale De Marco and has been published by Pasquale De Marco this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-06 with Mathematics categories.
In an era defined by uncertainty and complexity, Optimal Decision Statistics emerges as a beacon of clarity and guidance. This comprehensive and engaging book provides a thorough exploration of statistical decision theory and its wide-ranging applications, empowering readers to make informed and optimal decisions in the face of uncertainty. Written with clarity and rigor, Optimal Decision Statistics offers a systematic and accessible approach to understanding the fundamental principles of decision-making under uncertainty. Rooted in probability theory and statistical inference, this book equips readers with the tools and techniques necessary to navigate the complexities of decision-making in diverse scenarios. The book's comprehensive coverage encompasses a wide spectrum of topics, from the foundational concepts of probability theory and statistical inference to cutting-edge developments in decision statistics. Each chapter is meticulously crafted to build upon the preceding material, ensuring a smooth and comprehensive learning experience for readers of all backgrounds. Real-world examples and case studies are skillfully interwoven throughout the text, bringing the abstract concepts to life and showcasing the practical relevance of statistical decision theory in fields as varied as finance, medicine, engineering, and social sciences. These examples not only solidify the reader's understanding but also highlight the far-reaching impact of decision statistics in shaping our world. Optimal Decision Statistics is an invaluable resource for students, researchers, and practitioners seeking to deepen their understanding of decision-making under uncertainty. Its clear explanations, engaging writing style, and comprehensive coverage make it an indispensable guide for anyone looking to make informed and optimal decisions in the face of uncertainty. Whether you are a seasoned professional seeking to enhance your decision-making skills or a student eager to master the intricacies of statistical decision theory, Optimal Decision Statistics is the definitive guide to navigating the challenges of decision-making under uncertainty. If you like this book, write a review!
Optimal Decision Making In Operations Research And Statistics
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Author : Irfan Ali
language : en
Publisher: CRC Press
Release Date : 2021-11-29
Optimal Decision Making In Operations Research And Statistics written by Irfan Ali and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-29 with Business & Economics categories.
The book provides insights in the decision-making for implementing strategies in various spheres of real-world issues. It integrates optimal policies in various decisionmaking problems and serves as a reference for researchers and industrial practitioners. Furthermore, the book provides sound knowledge of modelling of real-world problems and solution procedure using the various optimisation and statistical techniques for making optimal decisions. The book is meant for teachers, students, researchers and industrialists who are working in the field of materials science, especially operations research and applied statistics.
Optimal Statistical Decisions
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Author : Morris H. DeGroot
language : en
Publisher: John Wiley & Sons
Release Date : 2005-01-28
Optimal Statistical Decisions written by Morris H. DeGroot 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 2005-01-28 with Mathematics categories.
The Wiley Classics Library consists of selected books that have become recognized classics in their respective fields. With these new unabridged and inexpensive editions, Wiley hopes to extend the life of these important works by making them available to future generations of mathematicians and scientists.
Methods Of Optimal Statistical Decisions Optimal Control And Stochastic Differential Equations
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Author : Ellida M. Khazen
language : en
Publisher: Xlibris Corporation
Release Date : 2009-11-16
Methods Of Optimal Statistical Decisions Optimal Control And Stochastic Differential Equations written by Ellida M. Khazen and has been published by Xlibris Corporation this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-11-16 with Education categories.
This book provides the reader with some insight into the mathematical models of random processes with continuous time, stochastic differential equations and stochastic integrals. An advanced development of the mathematical methods of optimal statistical decisions, statistical sequential analysis, and informational estimation of risks, and new methods and solutions to the important problems of the theory of optimal control are presented. The new original results obtained by this author and published shortly in her numerous scientific-research papers are presented in a systematic way in this book. The book is intended for engineers, students, post-graduate students, and scientist researchers. The presentation of the material is accessible to engineers.
Statistical Decision Theory
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Author : F. Liese
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-12-30
Statistical Decision Theory written by F. Liese 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 2008-12-30 with Mathematics categories.
For advanced graduate students, this book is a one-stop shop that presents the main ideas of decision theory in an organized, balanced, and mathematically rigorous manner, while observing statistical relevance. All of the major topics are introduced at an elementary level, then developed incrementally to higher levels. The book is self-contained as it provides full proofs, worked-out examples, and problems. The authors present a rigorous account of the concepts and a broad treatment of the major results of classical finite sample size decision theory and modern asymptotic decision theory. With its broad coverage of decision theory, this book fills the gap between standard graduate texts in mathematical statistics and advanced monographs on modern asymptotic theory.
Statistical Decision Problems
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Author : Michael Zabarankin
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-12-16
Statistical Decision Problems written by Michael Zabarankin 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 2013-12-16 with Business & Economics categories.
Statistical Decision Problems presents a quick and concise introduction into the theory of risk, deviation and error measures that play a key role in statistical decision problems. It introduces state-of-the-art practical decision making through twenty-one case studies from real-life applications. The case studies cover a broad area of topics and the authors include links with source code and data, a very helpful tool for the reader. In its core, the text demonstrates how to use different factors to formulate statistical decision problems arising in various risk management applications, such as optimal hedging, portfolio optimization, cash flow matching, classification, and more. The presentation is organized into three parts: selected concepts of statistical decision theory, statistical decision problems, and case studies with portfolio safeguard. The text is primarily aimed at practitioners in the areas of risk management, decision making, and statistics. However, the inclusion of a fair bit of mathematical rigor renders this monograph an excellent introduction to the theory of general error, deviation, and risk measures for graduate students. It can be used as supplementary reading for graduate courses including statistical analysis, data mining, stochastic programming, financial engineering, to name a few. The high level of detail may serve useful to applied mathematicians, engineers, and statisticians interested in modeling and managing risk in various applications.
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
Optimal Decisions Under Uncertainty
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Author : J.K. Sengupta
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Optimal Decisions Under Uncertainty written by J.K. Sengupta 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 Business & Economics categories.
Understanding the stochastic enviornment is as much important to the manager as to the economist. From production and marketing to financial management, a manager has to assess various costs imposed by uncertainty. The economist analyzes the role of incomplete and too often imperfect information structures on the optimal decisions made by a firm. The need for understanding the role of uncertainty in quantitative decision models, both in economics and management science provide the basic motivation of this monograph. The stochastic environment is analyzed here in terms of the following specific models of optimization: linear and quadratic models, linear programming, control theory and dynamic programming. Uncertainty is introduced here through the para meters, the constraints, and the objective function and its impact evaluated. Specifically recent developments in applied research are emphasized, so that they can help the decision-maker arrive at a solution which has some desirable charac teristics like robustness, stability and cautiousness. Mathematical treatment is kept at a fairly elementary level and applied as pects are emphasized much more than theory. Moreover, an attempt is made to in corporate the economic theory of uncertainty into the stochastic theory of opera tions research. Methods of optimal decision rules illustrated he re are applicable in three broad areas: (a) applied economic models in resource allocation and economic planning, (b) operations research models involving portfolio analysis and stochastic linear programming and (c) systems science models in stochastic control and adaptive behavior.
Statistical Experiments And Decision Asymptotic Theory
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Author : Albert N Shiryaev
language : en
Publisher: World Scientific
Release Date : 2000-07-04
Statistical Experiments And Decision Asymptotic Theory written by Albert N Shiryaev and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-07-04 with Mathematics categories.
This volume provides an exposition of some fundamental aspects of the asymptotic theory of statistical experiments. The most important of them is “how to construct asymptotically optimal decisions if we know the structure of optimal decisions for the limit experiment”.
Statistical Decision Rules And Optimal Inference
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Author :
language : en
Publisher:
Release Date : 1980
Statistical Decision Rules And Optimal Inference written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1980 with categories.