Countless professionals and students who use statistics in their work rely on the ten-volume (including supplement) Encyclopedia of Statistical Sciences as a superior and unique source of information on statistical theory, methods, and applications. This new volume is the first of three planned updates designed to bring the Encyclopedia in line with the latest topics and advances made in statistical science over the past decade—in areas such as computer-intensive statistical methodology, genetics, medicine, the environment, and other applications. 
Written by over 100 world-renowned experts (including the editors), the entries are self-contained and easily understood by readers with a limited statistical background. Up-to-date bibliographies, thorough cross-referencing, and extensive indexing facilitate quick access to specific information and provide an indispensable platform for further study and research. With the publication of this first update installment, the Encyclopedia of Statistical Sciences retains its position as a cutting-edge reference of choice for those working in statistics, biostatistics, quality control, economics, sociology, engineering, probability theory, computer science, biomedicine, psychology, and many other areas. Editorial Board

Encyclopedia of Statistical Sciences , Update (Volume 1)

Reference

Kotz, Samuel

Banks, David L.

Encyclopedias & Subject Guides

Wiley-Interscience

Encyclopedia of Statistical Sciences is the number one source of information on statistical theory, methods, and applications for researchers and clinicians. This new volume is the second of three updates designed to bring the Encyclopedia in line with new and emerging topics and important advances in statistical science made over the past decade. Each self-contained entry is written by a leader in the field and easily understood by readers with a modest statistical background. In addition to the main selections, which feature fascinating discussions of developments in various branches of the statistical sciences, readers will find a series of shorter entries ranging in subject matter from the lives of pioneers in statistics to updates of earlier articles and reviews of statistical agencies and journals. Up-to-date bibliographies, thorough cross-referencing, and extensive indexing facilitate quick access to specific information and provide an indispensable platform for further study and research. With the publication of this update installment, the Encyclopedia of Statistical Sciences retains its position as a cutting-edge reference of choice for those working in statistics, probability theory, biostatistics, quality control, and economics and in applications of statistical methods in sociology, engineering, computer science, biomedicine, psychology, and many other areas.

Encyclopedia of Statistical Sciences , Update Volume 2

Keeping pace with the latest developments in all branches of statistical science. Encyclopedia of Statistical Sciences is the number one source of information on statistical theory, methods, and applications for researchers and clinicians. This new volume is the last of three updates designed to bring the Encyclopedia in line with new and emerging topics and important advances in statistical science made over the past decade. Each self-contained entry is written by a leader in the field and easily understood by readers with a modest statistical background. In addition to the main selections, which feature fascinating discussions of developments in various branches of the statistical sciences, readers will find a series of shorter entries ranging in subject matter from the lives of pioneers in statistics to updates of earlier articles and reviews of statistical agencies and journals. Up-to-date bibliographies, thorough cross-referencing, and extensive indexing facilitate quick access to specific information and provide an indispensable platform for further study and research. A cumulative index and listing of all the entries in the 13 volumes of the Encyclopedia, together with the corresponding authors, are included. With the publication of this update installment, the Encyclopedia of Statistical Sciences retains its position as the only cutting-edge reference of choice for those working in statistics, probability theory, biostatistics, quality control, and economics and in applications of statistical methods in sociology, engineering, computer and communication science, biomedicine, psychology, and many other areas.

Encyclopedia of Statistical Sciences , Update (Wiley Series in Probability and Statistics) (Volume 3)

Science & Math

Mathematics

2 Become 1: Creating Memorable Moments to Deepen Your Marriage Connection

Susanne M. Alexander

Parenting & Relationships

Marriage Transformation LLC

Adversarial Risk Analysis

Product Description 
Winner of the 2017 De Groot Prize awarded by the International Society for Bayesian Analysis (ISBA)\nA relatively new area of research, adversarial risk analysis (ARA) informs decision making when there are intelligent opponents and uncertain outcomes. Adversarial Risk Analysis develops methods for allocating defensive or offensive resources against intelligent adversaries. Many examples throughout illustrate the application of the ARA approach to a variety of games and strategic situations.\nFocuses on the recent subfield of decision analysis, ARA \nCompares ideas from decision theory and game theory\nUses multi-agent influence diagrams (MAIDs) throughout to help readers visualize complex information structures\nApplies the ARA approach to simultaneous games, auctions, sequential games, and defend-attack games\nContains an extended case study based on a real application in railway security, which provides a blueprint for how to perform ARA in similar security situations \nIncludes exercises at the end of most chapters, with selected solutions at the back of the book\nThe book shows decision makers how to build Bayesian models for the strategic calculation of their opponents, enabling decision makers to maximize their expected utility or minimize their expected loss. This new approach to risk analysis asserts that analysts should use Bayesian thinking to describe their beliefs about an opponent’s goals, resources, optimism, and type of strategic calculation, such as minimax and level-k thinking. Within that framework, analysts then solve the problem from the perspective of the opponent while placing subjective probability distributions on all unknown quantities. This produces a distribution over the actions of the opponent and enables analysts to maximize their expected utilities. 
 Review 
"This well-written and concise text is an introduction to the field of adversarial risk analysis (ARA), which is a form of decision and risk analysis which incorporates uncertainty and game theory to model strategies of an adversary…There is an appropriate amount of detail throughout the book, making it suitable for a reference text as well as a book which may be read cover to cover and it is both thought provoking and enlightening."―Matthew Craven, Plymouth University, Journal of the Royal Statistical Society, Series A, January 2017 
"Here, Banks (Duke Univ.), Rios (IBM), and Insua (ICMAT-CSIC, Spain) identify three categories of uncertainty for the strategist: aleatory uncertainty―nondeterminism of outcomes even after players make choices; epistemic uncertainty―hidden information concerning opponents' preferences, beliefs, and capabilities; and concept uncertainty―hidden information concerning opponents' strategies. Adversarial risk analysis, a new field with roots in modern efforts to defeat terrorism, provides a framework, in principle, to cope with these uncertainties. Solving the models seems generally intractable, but the heart of the book, the first of its kind, offers exemplary case studies. Summing up: Recommended. Lower-division undergraduates and above; informed general audiences."―D. V. Feldman, University of New Hampshire, Durham, USA, for CHOICE, March 2016 
 About the Author 
David L. Banks is a professor in the Department of Statistical Science at Duke University. His research interests include data mining and risk analysis.\nJesus Rios is a researcher in risk and decision analytics for the Cognitive Computing Department at the IBM Research Division. His research focuses on applying risk and decision analysis to solve complex business problems.\nDavid Ríos Insua is the AXA-ICMAT Chair in Adversarial Risk Analysis at the Institute of Mathematical Sciences ICMAT-CSIC and a member of the Spanish Royal Academy of Sciences. His research interests include risk analysis, decision analysis, Bayesian statistics, security, aviation safety, and social robotics.

Aliaga, Jesus M. Rios

Rios Insua, David

Routledge

Winner of the 2017 De Groot Prize awarded by the International Society for Bayesian Analysis (ISBA) A relatively new area of research, adversarial risk analysis (ARA) informs decision making when there are intelligent opponents and uncertain outcomes. Adversarial Risk Analysis develops methods for allocating defensive or offensive resources against intelligent adversaries. Many examples throughout illustrate the application of the ARA approach to a variety of games and strategic situations. <li>Focuses on the recent subfield of decision analysis, ARA </li> <li>Compares ideas from decision theory and game theory</li> <li>Uses multi-agent influence diagrams (MAIDs) throughout to help readers visualize complex information structures</li> <li>Applies the ARA approach to simultaneous games, auctions, sequential games, and defend-attack games</li> <li>Contains an extended case study based on a real application in railway security, which provides a blueprint for how to perform ARA in similar security situations </li> <li>Includes exercises at the end of most chapters, with selected solutions at the back of the book</li> The book shows decision makers how to build Bayesian models for the strategic calculation of their opponents, enabling decision makers to maximize their expected utility or minimize their expected loss. This new approach to risk analysis asserts that analysts should use Bayesian thinking to describe their beliefs about an opponent’s goals, resources, optimism, and type of strategic calculation, such as minimax and level-k thinking. Within that framework, analysts then solve the problem from the perspective of the opponent while placing subjective probability distributions on all unknown quantities. This produces a distribution over the actions of the opponent and enables analysts to maximize their expected utilities.

Chapman and Hall/CRC

Fort Whiskey: Mordecai's Crossing

Literature & Fiction

Action & Adventure

Davo

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