The Oxford Handbook of Applied Bayesian Analysis

Author: Anthony O' Hagan,Mike West

Publisher: OUP Oxford

ISBN: 0191613894

Category: Mathematics

Page: 924

View: 9562

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Bayesian analysis has developed rapidly in applications in the last two decades and research in Bayesian methods remains dynamic and fast-growing. Dramatic advances in modelling concepts and computational technologies now enable routine application of Bayesian analysis using increasingly realistic stochastic models, and this drives the adoption of Bayesian approaches in many areas of science, technology, commerce, and industry. This Handbook explores contemporary Bayesian analysis across a variety of application areas. Chapters written by leading exponents of applied Bayesian analysis showcase the scientific ease and natural application of Bayesian modelling, and present solutions to real, engaging, societally important and demanding problems. The chapters are grouped into five general areas: Biomedical & Health Sciences; Industry, Economics & Finance; Environment & Ecology; Policy, Political & Social Sciences; and Natural & Engineering Sciences, and Appendix material in each touches on key concepts, models, and techniques of the chapter that are also of broader pedagogic and applied interest.
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The Oxford Handbook of Bayesian Econometrics

Author: John Geweke,Gary Koop,Herman van Dijk

Publisher: Oxford University Press

ISBN: 0199559082

Category: Business & Economics

Page: 558

View: 7647

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A broad coverage of the application of Bayesian econometrics in the major fields of economics and related disciplines, including macroeconomics, microeconomics, finance, and marketing.
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The Oxford Handbook of Quantitative Methods in Psychology

Foundations

Author: Todd D. Little

Publisher: Oxford University Press, USA

ISBN: 019937015X

Category: Psychology

Page: 515

View: 1692

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This two-volume handbook on current best-practices in quantitative methods as practiced in the social, behavioral, and educational sciences covers philosophical and ethical issues, theory construction, model building and types of models, survey and experiment design, measurement issues, observational methods, statistical methods, types of analysis, types of data, and common research fallacies.
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The Oxford Handbook of Quantitative Asset Management

Author: Bernd Scherer,Kenneth Winston

Publisher: OUP Oxford

ISBN: 0191624055

Category: Business & Economics

Page: 536

View: 7333

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Quantitative portfolio management has become a highly specialized discipline. Computing power and software improvements have advanced the field to a level that would not have been thinkable when Harry Markowitz began the modern era of quantitative portfolio management in 1952. In addition to raw computing power, major advances in financial economics and econometrics have shaped academia and the financial industry over the last 60 years. While the idea of a general theory of finance is still only a distant hope, asset managers now have tools in the financial engineering kit that address specific problems in their industry. The Oxford Handbook of Quantitative Asset Management consists of seven sections that explore major themes in current theoretical and practical use. These themes span all aspects of a modern quantitative investment organization. Contributions from academics and practitioners working in leading investment management organizations bring together the key theoretical and practical aspects of the field to provide a comprehensive overview of the major developments in the area.
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The Oxford Handbook of Quantitative Methods, Volume 1: Foundations

Author: Todd D. Little

Publisher: Oxford University Press

ISBN: 0199934886

Category: Psychology

Page: 506

View: 7214

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Research today demands the application of sophisticated and powerful research tools. Fulfilling this need, The Oxford Handbook of Quantitative Methods is the complete tool box to deliver the most valid and generalizable answers to todays complex research questions. It is a one-stop source for learning and reviewing current best-practices in quantitative methods as practiced in the social, behavioral, and educational sciences. Comprising two volumes, this handbook covers a wealth of topics related to quantitative research methods. It begins with essential philosophical and ethical issues related to science and quantitative research. It then addresses core measurement topics before delving into the design of studies. Principal issues related to modern estimation and mathematical modeling are also detailed. Topics in the handbook then segway into the realm of statistical inference and modeling with chapters dedicated to classical approaches as well as modern latent variable approaches. Numerous chapters associated with longitudinal data and more specialized techniques round out this broad selection of topics. Comprehensive, authoritative, and user-friendly, this two-volume set will be an indispensable resource for serious researchers across the social, behavioral, and educational sciences.
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The Oxford Handbook of Quantitative Methods, Vol. 2: Statistical Analysis

Author: Todd D. Little

Publisher: Oxford University Press

ISBN: 0199934908

Category: Psychology

Page: 784

View: 778

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Research today demands the application of sophisticated and powerful research tools. Fulfilling this need, The Oxford Handbook of Quantitative Methods is the complete tool box to deliver the most valid and generalizable answers to todays complex research questions. It is a one-stop source for learning and reviewing current best-practices in quantitative methods as practiced in the social, behavioral, and educational sciences. Comprising two volumes, this handbook covers a wealth of topics related to quantitative research methods. It begins with essential philosophical and ethical issues related to science and quantitative research. It then addresses core measurement topics before delving into the design of studies. Principal issues related to modern estimation and mathematical modeling are also detailed. Topics in the handbook then segway into the realm of statistical inference and modeling with chapters dedicated to classical approaches as well as modern latent variable approaches. Numerous chapters associated with longitudinal data and more specialized techniques round out this broad selection of topics. Comprehensive, authoritative, and user-friendly, this two-volume set will be an indispensable resource for serious researchers across the social, behavioral, and educational sciences.
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The Oxford Handbook of 4E Cognition

Author: Albert Newen,Leon De Bruin,Shaun Gallagher

Publisher: Oxford University Press

ISBN: 0191054356

Category: Psychology

Page: 952

View: 1172

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4E cognition (embodied, embedded, enactive, and extended) is a relatively young and thriving field of interdisciplinary research. It assumes that cognition is shaped and structured by dynamic interactions between the brain, body, and both the physical and social environments. With essays from leading scholars and researchers, The Oxford Handbook of 4E Cognition investigates this recent paradigm. It addresses the central issues of embodied cognition by focusing on recent trends, such as Bayesian inference and predictive coding, and presenting new insights, such as the development of false belief understanding. The Oxford Handbook of 4E Cognition also introduces new theoretical paradigms for understanding emotion and conceptualizing the interactions between cognition, language, and culture. With an entire section dedicated to the application of 4E cognition in disciplines such as psychiatry and robotics, and critical notes aimed at stimulating discussion, this Oxford handbook is the definitive guide to 4E cognition. Aimed at neuroscientists, psychologists, psychiatrists, and philosophers, The Oxford Handbook of 4E Cognition will be essential reading for anyone with an interest in this young and thriving field.
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Bayesian Econometric Methods

Author: Joshua Chan,Gary Koop,Dale J. Poirier,Justin L. Tobias

Publisher: Cambridge University Press

ISBN: 1108423388

Category: Business & Economics

Page: 480

View: 1991

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Illustrates Bayesian theory and application through a series of exercises in question and answer format.
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Data Analysis

A Bayesian Tutorial

Author: D. S. Sivia

Publisher: Oxford University Press

ISBN: 9780198518891

Category: Science

Page: 189

View: 9496

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Statistics lectures have often been viewed with trepidation by engineering and science students taking an ancillary course in this subject. Whereas there are many texts showing "how" statistical methods are applied, few provide a clear explanation for non-statisticians of how the principlesof data analysis can be based on probability theory. Data Analysis: A Bayesian Tutorial provides such a text, putting emphasis as much on understanding "why" and "when" certain statistical procedures should be used as "how". This difference in approach makes the text ideal as a tutorial guide forsenior undergraduates and research students, in science and engineering. After explaining the basic principles of Bayesian probability theory, their use is illustrated with a variety of examples ranging from elementary parameter estimation to image processing. With its central emphasis on a fewfundamental rules, this book takes the mystery out of statistics by providing a clear rationale for some of the most widely-used procedures.
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Data Analysis

A Bayesian Tutorial

Author: Devinderjit Sivia,John Skilling

Publisher: Oxford University Press

ISBN: 0198568312

Category: Mathematics

Page: 246

View: 4298

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Statistics lectures have been a source of much bewilderment and frustration for generations of students. This book attempts to remedy the situation by expounding a logical and unified approach to the whole subject of data analysis. This text is intended as a tutorial guide for senior undergraduates and research students in science and engineering. After explaining the basic principles of Bayesian probability theory, their use is illustrated with a variety of examples ranging from elementary parameter estimation to image processing. Other topics covered include reliability analysis, multivariate optimization, least-squares and maximum likelihood, error-propagation, hypothesis testing, maximum entropy and experimental design. The Second Edition of this successful tutorial book contains a new chapter on extensions to the ubiquitous least-squares procedure, allowing for the straightforward handling of outliers and unknown correlated noise, and a cutting-edge contribution from John Skilling on a novel numerical technique for Bayesian computation called 'nested sampling'.
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