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Causal Analytics for Applied Risk Analysis, Louis Anthony Cox Jr.; Douglas A. Popken; Richard


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Цена: 41925.00р.
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Автор: Louis Anthony Cox Jr.; Douglas A. Popken; Richard
Название:  Causal Analytics for Applied Risk Analysis
ISBN: 9783030086534
Издательство: Springer
Классификация:


ISBN-10: 3030086534
Обложка/Формат: Soft cover
Страницы: 588
Вес: 0.93 кг.
Дата издания: 2019
Серия: International Series in Operations Research & Management Science
Язык: English
Издание: Softcover reprint of
Иллюстрации: 123 tables, color; 95 illustrations, color; 26 illustrations, black and white; xxii, 588 p. 121 illus., 95 illus. in color.
Размер: 234 x 156 x 32
Читательская аудитория: General (us: trade)
Ключевые слова: Operations Research/Decision Theory
Основная тема: Business and Management
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Causal analytics methods can revolutionize the use of data to make effective decisions by revealing how different choices affect probabilities of various outcomes. This book presents and illustrates models, algorithms, principles, and software for deriving causal models from data and for using them to optimize decisions with uncertain outcomes. It discusses how to describe and summarize situations; detect changes; evaluate effects of policies or interventions; learn what works best under different conditions; predict values of as-yet unobserved quantities from available data; and identify the most likely explanations for observed outcomes, including surprises and anomalies. The book resents practical techniques for causal modeling and analytics that practitioners can apply to improve understanding of how choices affect probabilities of consequences and, based on this understanding, to recommend choices that are more likely to accomplish their intended objectives.
The book begins with a survey of modern analytics methods, focusing mainly on techniques useful for decision, risk, and policy analysis. Chapter 2 introduces free in-browser software, including the Causal Analytics Toolkit (CAT) software, to enable readers to perform the analyses described and to apply modern analytics methods easily to their own data sets. Chapters 3 through 11 show how to apply causal analytics and risk analytics to practical risk analysis challenges, mainly related to public and occupational health risks from pathogens in food or from pollutants in air. Chapters 12 through 15 turn to broader questions of how to improve risk management decision-making by individuals, groups, organizations, institutions, and multi-generation societies with different cultures and norms for cooperation. These chapters examine organizational learning, community resilience, societal risk management, and intergenerational collaboration and justice in managing risks.

Дополнительное описание: Part 1. Concepts and Methods of Causal Analytics.- Chapter 1. Causal Analytics and Risk Analytics.- Chapter 2. Causal Concepts, Principles, and Algorithms.- Part 2. Descriptive Analytics in Public and Occupational Health.- Chapter 3. Descriptive Analytics



Causal Analytics for Applied Risk Analysis

Автор: Cox Jr.
Название: Causal Analytics for Applied Risk Analysis
ISBN: 3319782401 ISBN-13(EAN): 9783319782409
Издательство: Springer
Рейтинг:
Цена: 41925.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Causal analytics methods can revolutionize the use of data to make effective decisions by revealing how different choices affect probabilities of various outcomes. This book presents and illustrates models, algorithms, principles, and software for deriving causal models from data and for using them to optimize decisions with uncertain outcomes. It discusses how to describe and summarize situations; detect changes; evaluate effects of policies or interventions; learn what works best under different conditions; predict values of as-yet unobserved quantities from available data; and identify the most likely explanations for observed outcomes, including surprises and anomalies. The book resents practical techniques for causal modeling and analytics that practitioners can apply to improve understanding of how choices affect probabilities of consequences and, based on this understanding, to recommend choices that are more likely to accomplish their intended objectives.

The book begins with a survey of modern analytics methods, focusing mainly on techniques useful for decision, risk, and policy analysis. Chapter 2 introduces free in-browser software, including the Causal Analytics Toolkit (CAT) software, to enable readers to perform the analyses described and to apply modern analytics methods easily to their own data sets. Chapters 3 through 11 show how to apply causal analytics and risk analytics to practical risk analysis challenges, mainly related to public and occupational health risks from pathogens in food or from pollutants in air. Chapters 12 through 15 turn to broader questions of how to improve risk management decision-making by individuals, groups, organizations, institutions, and multi-generation societies with different cultures and norms for cooperation. These chapters examine organizational learning, community resilience, societal risk management, and intergenerational collaboration and justice in managing risks.
Handbook of Operations Analytics Using Data Envelopment Analysis

Автор: Hwang
Название: Handbook of Operations Analytics Using Data Envelopment Analysis
ISBN: 1489977031 ISBN-13(EAN): 9781489977038
Издательство: Springer
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Цена: 20962.00 р.
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Описание: This handbook focuses on Data Envelopment Analysis (DEA) applications in operations analytics which are fundamental tools and techniques for improving operation functions and attaining long-term competitiveness. In fact, the handbook demonstrates that DEA can be viewed as Data Envelopment Analytics.Chapters include a review of cross-efficiency evaluation; a case study on measuring the environmental performance of OECS countries; how to select a set of performance metrics in DEA with an application to American banks; a relational network model to take the operations of individual periods into account in measuring efficiencies; how the efficient frontier methods DEA and stochastic frontier analysis (SFA) can be used synergistically; and how to integrate DEA and multidimensional scaling.In other chapters, authors construct a dynamic three-stage network DEA model; a bootstrapping based methodology to evaluate returns to scale and convexity assumptions in DEA; hybridizing DEA and cooperative games; using DEA to represent the production technology and directional distance functions to measure band performance; an input-specific Luenberger energy and environmental productivity indicator; and the issue of reference set by differentiating between the uniquely found reference set and the unary and maximal types of the reference set.Finally, additional chapters evaluate and compare the technological advancement observed in different hybrid electric vehicles (HEV) market segments over the past 15 years; radial measurement of efficiency for the production process possessing multi-components under different production technologies; issues around the use of accounting information in DEA; how to use DEA environmental assessment to establish corporate sustainability; a summary of research efforts on DEA environmental assessment applied to energy in the last 30 years; and an overview of DEA and how it can be utilized alone and with other techniques to investigate corporate environmental sustainability questions.

Applied big data analytics in operations management /

Название: Applied big data analytics in operations management /
ISBN: 1522508864 ISBN-13(EAN): 9781522508861
Издательство: Turpin
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Цена: 23654.00 р.
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Описание: Operations management is a tool by which companies can effectively meet customers’ needs using the least amount of resources necessary. With the emergence of sensors and smart metering, big data is becoming an intrinsic part of modern operations management.Applied Big Data Analytics in Operations Management enumerates the challenges and creative solutions and tools to apply when using big data in operations management. Outlining revolutionary concepts and applications that help businesses predict customer behavior along with applications of artificial neural networks, predictive analytics, and opinion mining on business management, this comprehensive publication is ideal for IT professionals, software engineers, business professionals, managers, and students of management.

Causal Models and Intelligent Data Management

Автор: Alex Gammerman
Название: Causal Models and Intelligent Data Management
ISBN: 3642636829 ISBN-13(EAN): 9783642636820
Издательство: Springer
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Цена: 6986.00 р.
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Описание: The need to electronically store, manipulate and analyze large-scale, high-dimensional data sets requires new computational methods. This book presents new intelligent data management methods and tools, including new results from the field of inference.

The Causal Structure of Long-Term Supply Relationships

Автор: Gjalt de Jong; Bart Nooteboom
Название: The Causal Structure of Long-Term Supply Relationships
ISBN: 1461370418 ISBN-13(EAN): 9781461370413
Издательство: Springer
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Цена: 20962.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: In the past decades, research on strategic alliances -the class of interfirm arrangements to which long-term supply relationships belong- mushroomed. On the contrary, because of all these studies we now have some knowledge about the reasons why firms enter in alliances and why some alliances are more successful than others.

Applied Statistics and Multivariate Data Analysis

Автор: Thomas Cleff
Название: Applied Statistics and Multivariate Data Analysis
ISBN: 3030177661 ISBN-13(EAN): 9783030177669
Издательство: Springer
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Цена: 9083.00 р.
Наличие на складе: Поставка под заказ.

Описание: This textbook will familiarize students in economics and business, as well as practitioners, with the basic principles, techniques, and applications of applied statistics, statistical testing, and multivariate data analysis.

Robustness Analysis in Decision Aiding, Optimization, and Analytics

Автор: Doumpos
Название: Robustness Analysis in Decision Aiding, Optimization, and Analytics
ISBN: 3319331191 ISBN-13(EAN): 9783319331195
Издательство: Springer
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Цена: 19564.00 р.
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Описание:

This book provides a broad coverage of the recent advances in robustness analysis in decision aiding, optimization, and analytics. It offers a comprehensive illustration of the challenges that robustness raises in different operations research and management science (OR/MS) contexts and the methodologies proposed from multiple perspectives. Aside from covering recent methodological developments, this volume also features applications of robust techniques in engineering and management, thus illustrating the robustness issues raised in real-world problems and their resolution within advances in OR/MS methodologies.
Robustness analysis seeks to address issues by promoting solutions, which are acceptable under a wide set of hypotheses, assumptions and estimates. In OR/MS, robustness has been mostly viewed in the context of optimization under uncertainty. Several scholars, however, have emphasized the multiple facets of robustness analysis in a broader OR/MS perspective that goes beyond the traditional framework, seeking to cover the decision support nature of OR/MS methodologies as well. As new challenges emerge in a “big-data'” era, where the information volume, speed of flow, and complexity increase rapidly, and analytics play a fundamental role for strategic and operational decision-making at a global level, robustness issues such as the ones covered in this book become more relevant than ever for providing sound decision support through more powerful analytic tools.
Business Analytics: Data Analysis & Decision Making

Автор: Albright S. Christian, Winston Wayne L.
Название: Business Analytics: Data Analysis & Decision Making
ISBN: 0357109953 ISBN-13(EAN): 9780357109953
Издательство: Cengage Learning
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Цена: 12670.00 р.
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Описание: Master data analysis, modeling and the effective use of spreadsheets with the popular BUSINESS ANALYTICS: DATA ANALYSIS AND DECISION MAKING, 7E. The quantitative methods approach in this edition helps you maximize your success with a proven teach-by-example presentation, inviting writing style and complete integration of the latest version of Excel. The approach is also compatible with earlier versions of Excel for your convenience.

This edition is more data-oriented than ever before with a new chapter on the two main Power BI tools in Excel -- Power Query and Power Pivot -- and a new section of data visualization with Tableau Public. Current problems and cases demonstrate the importance of the concepts you are learning. In addition, a useful Companion Website provides data and solutions files, SolverTable for optimization sensitivity analysis and Palisade DecisionTools Suite.

MindTap online resources are also available.

Managerial Perspectives on Intelligent Big Data Analytics

Автор: Zhaohao Sun
Название: Managerial Perspectives on Intelligent Big Data Analytics
ISBN: 1522572775 ISBN-13(EAN): 9781522572770
Издательство: Mare Nostrum (Eurospan)
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Цена: 32987.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Big data, analytics, and artificial intelligence are revolutionizing work, management, and lifestyles and are becoming disruptive technologies for healthcare, e-commerce, and web services. However, many fundamental, technological, and managerial issues for developing and applying intelligent big data analytics in these fields have yet to be addressed. Managerial Perspectives on Intelligent Big Data Analytics is a collection of innovative research that discusses the integration and application of artificial intelligence, business intelligence, digital transformation, and intelligent big data analytics from a perspective of computing, service, and management. While highlighting topics including e-commerce, machine learning, and fuzzy logic, this book is ideally designed for students, government officials, data scientists, managers, consultants, analysts, IT specialists, academicians, researchers, and industry professionals in fields that include big data, artificial intelligence, computing, and commerce.

Applied Analytics through Case Studies Using SAS and R

Автор: Gupta
Название: Applied Analytics through Case Studies Using SAS and R
ISBN: 148423524X ISBN-13(EAN): 9781484235249
Издательство: Springer
Рейтинг:
Цена: 8384.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Examine business problems and use a practical analytical approach to solve them by implementing predictive models and machine learning techniques using SAS and the R analytical language.

This book is ideal for those who are well-versed in writing code and have a basic understanding of statistics, but have limited experience in implementing predictive models and machine learning techniques for analyzing real world data. The most challenging part of solving industrial business problems is the practical and hands-on knowledge of building and deploying advanced predictive models and machine learning algorithms.
Applied Analytics through Case Studies Using SAS and R is your answer to solving these business problems by sharpening your analytical skills.
What You'll Learn
Understand analytics and basic data concepts Use an analytical approach to solve Industrial business problems Build predictive model with machine learning techniquesCreate and apply analytical strategies
Who This Book Is For
Data scientists, developers, statisticians, engineers, and research students with a great theoretical understanding of data and statistics who would like to enhance their skills by getting practical exposure in data modeling.
Institute of mathematical statistics textbooks

Автор: Nualart, David (university Of Kansas) Nualart, Eul...lia (universitat Pompeu Fabra, Barcelona)
Название: Institute of mathematical statistics textbooks
ISBN: 1107611989 ISBN-13(EAN): 9781107611986
Издательство: Cambridge Academ
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Цена: 6019.00 р.
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Описание: This textbook offers a compact introduction to Malliavin calculus. It covers recent applications, and includes a self-contained presentation of preliminary material on Brownian motion and stochastic calculus. Accessible to non-experts, graduate students and researchers can use this book to master the core techniques necessary for further study.

Nonlinear Programming: An Introduction

Автор: Peter Zornig
Название: Nonlinear Programming: An Introduction
ISBN: 3110315270 ISBN-13(EAN): 9783110315271
Издательство: Walter de Gruyter
Цена: 9288.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание:

This book is an introduction to nonlinear programming. It deals with the theoretical foundations and solution methods, beginning with the classical procedures and reaching up to -modern- methods like trust region methods or procedures for nonlinear and global optimization. A comprehensive bibliography including diverse web sites with information about nonlinear programming, in particular software, is presented. Without sacrificing the necessary mathematical rigor, excessive formalisms are avoided. Several examples, exercises with detailed solutions, and applications are provided, making the text adequate for individual studies.

The book is written for students from the fields of applied mathematics, engineering, economy, and computation.


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