Bayesian Methods For Management And Business

Author : Eugene D. Hahn
Publisher : John Wiley & Sons
Page : 384 pages
File Size : 52,6 Mb
Release : 2014-09-02
Category : Mathematics
ISBN : 9781118637562

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Bayesian Methods for Management and Business by Eugene D. Hahn Pdf

HIGHLIGHTS THE USE OF BAYESIAN STATISTICS TO GAIN INSIGHTS FROM EMPIRICAL DATA Featuring an accessible approach, Bayesian Methods for Management and Business: Pragmatic Solutions for Real Problems demonstrates how Bayesian statistics can help to provide insights into important issues facing business and management. The book draws on multidisciplinary applications and examples and utilizes the freely available software WinBUGS and R to illustrate the integration of Bayesian statistics within data-rich environments. Computational issues are discussed and integrated with coverage of linear models, sensitivity analysis, Markov Chain Monte Carlo (MCMC), and model comparison. In addition, more advanced models including hierarchal models, generalized linear models, and latent variable models are presented to further bridge the theory and application in real-world usage. Bayesian Methods for Management and Business: Pragmatic Solutions for Real Problems also features: Numerous real-world examples drawn from multiple management disciplines such as strategy, international business, accounting, and information systems An incremental skill-building presentation based on analyzing data sets with widely applicable models of increasing complexity An accessible treatment of Bayesian statistics that is integrated with a broad range of business and management issues and problems A practical problem-solving approach to illustrate how Bayesian statistics can help to provide insight into important issues facing business and management Bayesian Methods for Management and Business: Pragmatic Solutions for Real Problems is an important textbook for Bayesian statistics courses at the advanced MBA-level and also for business and management PhD candidates as a first course in methodology. In addition, the book is a useful resource for management scholars and practitioners as well as business academics and practitioners who seek to broaden their methodological skill sets.

Author : Sylvia Frühwirth-Schnatter,Angela Bitto,Gregor Kastner,Alexandra Posekany
Publisher : Springer
Page : 167 pages
File Size : 42,6 Mb
Release : 2015-05-19
Category : Mathematics
ISBN : 9783319162386

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Bayesian Statistics from Methods to Models and Applications by Sylvia Frühwirth-Schnatter,Angela Bitto,Gregor Kastner,Alexandra Posekany Pdf

The Second Bayesian Young Statisticians Meeting (BAYSM 2014) and the research presented here facilitate connections among researchers using Bayesian Statistics by providing a forum for the development and exchange of ideas. WU Vienna University of Business and Economics hosted BAYSM 2014 from September 18th to the 19th. The guidance of renowned plenary lecturers and senior discussants is a critical part of the meeting and this volume, which follows publication of contributions from BAYSM 2013. The meeting's scientific program reflected the variety of fields in which Bayesian methods are currently employed or could be introduced in the future. Three brilliant keynote lectures by Chris Holmes (University of Oxford), Christian Robert (Université Paris-Dauphine), and Mike West (Duke University), were complemented by 24 plenary talks covering the major topics Dynamic Models, Applications, Bayesian Nonparametrics, Biostatistics, Bayesian Methods in Economics, and Models and Methods, as well as a lively poster session with 30 contributions. Selected contributions have been drawn from the conference for this book. All contributions in this volume are peer-reviewed and share original research in Bayesian computation, application, and theory.

Author : Svetlozar T. Rachev,John S. J. Hsu,Biliana S. Bagasheva,Frank J. Fabozzi
Publisher : John Wiley & Sons
Page : 351 pages
File Size : 48,9 Mb
Release : 2008-02-13
Category : Business & Economics
ISBN : 9780470249246

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Bayesian Methods in Finance by Svetlozar T. Rachev,John S. J. Hsu,Biliana S. Bagasheva,Frank J. Fabozzi Pdf

Bayesian Methods in Finance provides a detailed overview of the theory of Bayesian methods and explains their real-world applications to financial modeling. While the principles and concepts explained throughout the book can be used in financial modeling and decision making in general, the authors focus on portfolio management and market risk management—since these are the areas in finance where Bayesian methods have had the greatest penetration to date.

Author : David Ardia
Publisher : Springer Science & Business Media
Page : 206 pages
File Size : 40,6 Mb
Release : 2008-05-08
Category : Business & Economics
ISBN : 9783540786573

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Financial Risk Management with Bayesian Estimation of GARCH Models by David Ardia Pdf

This book presents in detail methodologies for the Bayesian estimation of sing- regime and regime-switching GARCH models. These models are widespread and essential tools in n ancial econometrics and have, until recently, mainly been estimated using the classical Maximum Likelihood technique. As this study aims to demonstrate, the Bayesian approach o ers an attractive alternative which enables small sample results, robust estimation, model discrimination and probabilistic statements on nonlinear functions of the model parameters. The author is indebted to numerous individuals for help in the preparation of this study. Primarily, I owe a great debt to Prof. Dr. Philippe J. Deschamps who inspired me to study Bayesian econometrics, suggested the subject, guided me under his supervision and encouraged my research. I would also like to thank Prof. Dr. Martin Wallmeier and my colleagues of the Department of Quantitative Economics, in particular Michael Beer, Roberto Cerratti and Gilles Kaltenrieder, for their useful comments and discussions. I am very indebted to my friends Carlos Ord as Criado, Julien A. Straubhaar, J er ^ ome Ph. A. Taillard and Mathieu Vuilleumier, for their support in the elds of economics, mathematics and statistics. Thanks also to my friend Kevin Barnes who helped with my English in this work. Finally, I am greatly indebted to my parents and grandparents for their support and encouragement while I was struggling with the writing of this thesis.

Author : Anonim
Publisher : Academic Press
Page : 322 pages
File Size : 54,6 Mb
Release : 2022-10-06
Category : Mathematics
ISBN : 9780323952699

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Advancements in Bayesian Methods and Implementations by Anonim Pdf

Advancements in Bayesian Methods and Implementation, Volume 47 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of timely topics, including Fisher Information, Cramer-Rao and Bayesian Paradigm, Compound beta binomial distribution functions, MCMC for GLMMS, Signal Processing and Bayesian, Mathematical theory of Bayesian statistics where all models are wrong, Machine Learning and Bayesian, Non-parametric Bayes, Bayesian testing, and Data Analysis with humans, Variational inference or Functional horseshoe, Generalized Bayes. Provides the authority and expertise of leading contributors from an international board of authors Presents the latest release in the Handbook of Statistics series Updated release includes the latest information on Advancements in Bayesian Methods and Implementation

Author : Peter E. Rossi,Greg M. Allenby,Rob McCulloch
Publisher : John Wiley & Sons
Page : 368 pages
File Size : 52,8 Mb
Release : 2012-05-14
Category : Mathematics
ISBN : 9780470863688

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Bayesian Statistics and Marketing by Peter E. Rossi,Greg M. Allenby,Rob McCulloch Pdf

The past decade has seen a dramatic increase in the use of Bayesian methods in marketing due, in part, to computational and modelling breakthroughs, making its implementation ideal for many marketing problems. Bayesian analyses can now be conducted over a wide range of marketing problems, from new product introduction to pricing, and with a wide variety of different data sources. Bayesian Statistics and Marketing describes the basic advantages of the Bayesian approach, detailing the nature of the computational revolution. Examples contained include household and consumer panel data on product purchases and survey data, demand models based on micro-economic theory and random effect models used to pool data among respondents. The book also discusses the theory and practical use of MCMC methods. Written by the leading experts in the field, this unique book: Presents a unified treatment of Bayesian methods in marketing, with common notation and algorithms for estimating the models. Provides a self-contained introduction to Bayesian methods. Includes case studies drawn from the authors’ recent research to illustrate how Bayesian methods can be extended to apply to many important marketing problems. Is accompanied by an R package, bayesm, which implements all of the models and methods in the book and includes many datasets. In addition the book’s website hosts datasets and R code for the case studies. Bayesian Statistics and Marketing provides a platform for researchers in marketing to analyse their data with state-of-the-art methods and develop new models of consumer behaviour. It provides a unified reference for cutting-edge marketing researchers, as well as an invaluable guide to this growing area for both graduate students and professors, alike.

Author : Matt Sekerke
Publisher : John Wiley & Sons
Page : 240 pages
File Size : 45,8 Mb
Release : 2015-08-19
Category : Business & Economics
ISBN : 9781118747452

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Bayesian Risk Management by Matt Sekerke Pdf

A risk measurement and management framework that takes model risk seriously Most financial risk models assume the future will look like the past, but effective risk management depends on identifying fundamental changes in the marketplace as they occur. Bayesian Risk Management details a more flexible approach to risk management, and provides tools to measure financial risk in a dynamic market environment. This book opens discussion about uncertainty in model parameters, model specifications, and model-driven forecasts in a way that standard statistical risk measurement does not. And unlike current machine learning-based methods, the framework presented here allows you to measure risk in a fully-Bayesian setting without losing the structure afforded by parametric risk and asset-pricing models. Recognize the assumptions embodied in classical statistics Quantify model risk along multiple dimensions without backtesting Model time series without assuming stationarity Estimate state-space time series models online with simulation methods Uncover uncertainty in workhorse risk and asset-pricing models Embed Bayesian thinking about risk within a complex organization Ignoring uncertainty in risk modeling creates an illusion of mastery and fosters erroneous decision-making. Firms who ignore the many dimensions of model risk measure too little risk, and end up taking on too much. Bayesian Risk Management provides a roadmap to better risk management through more circumspect measurement, with comprehensive treatment of model uncertainty.

Author : Narayanaswamy Balakrishnan
Publisher : John Wiley & Sons
Page : 735 pages
File Size : 49,9 Mb
Release : 2010-07-13
Category : Mathematics
ISBN : 9780470405109

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Methods and Applications of Statistics in Business, Finance, and Management Science by Narayanaswamy Balakrishnan Pdf

Inspired by the Encyclopedia of Statistical Sciences, Second Edition, this volume presents the tools and techniques that are essential for carrying out best practices in the modern business world The collection and analysis of quantitative data drives some of the most important conclusions that are drawn in today's business world, such as the preferences of a customer base, the quality of manufactured products, the marketing of products, and the availability of financial resources. As a result, it is essential for individuals working in this environment to have the knowledge and skills to interpret and use statistical techniques in various scenarios. Addressing this need, Methods and Applications of Statistics in Business, Finance, and Management Science serves as a single, one-of-a-kind resource that guides readers through the use of common statistical practices by presenting real-world applications from the fields of business, economics, finance, operations research, and management science. Uniting established literature with the latest research, this volume features classic articles from the acclaimed Encyclopedia of Statistical Sciences, Second Edition along with brand-new contributions written by today's leading academics and practitioners. The result is a compilation that explores classic methodology and new topics, including: Analytical methods for risk management Statistical modeling for online auctions Ranking and selection in mutual funds Uses of Black-Scholes formula in finance Data mining in prediction markets From auditing and marketing to stock market price indices and banking, the presented literature sheds light on the use of quantitative methods in research relating to common financial applications. In addition, the book supplies insight on common uses of statistical techniques such as Bayesian methods, optimization, simulation, forecasting, mathematical modeling, financial time series, and data mining in modern research. Providing a blend of traditional methodology and the latest research, Methods and Applications of Statistics in Business, Finance, and Management Science is an excellent reference for researchers, managers, consultants, and students in the fields of business, management science, operations research, supply chain management, mathematical finance, and economics who must understand statistical literature and carry out quantitative practices to make smart business decisions in their everyday work.

Author : Anonim
Publisher : Unknown
Page : 329 pages
File Size : 46,7 Mb
Release : 2008
Category : Bayesian statistical decision theory
ISBN : 1119202140

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Bayesian Methods in Finance by Anonim Pdf

Provides an overview of the theory and practice of Bayesian methods in finance. This book explains and illustrates the foundations of the Bayesian methodology and provides a unified examination of the use of the Bayesian theory and practice to analyze and evaluate asset management.

Author : Andrew Gelman,John B. Carlin,Hal S. Stern,David B. Dunson,Aki Vehtari,Donald B. Rubin
Publisher : CRC Press
Page : 677 pages
File Size : 41,8 Mb
Release : 2013-11-01
Category : Mathematics
ISBN : 9781439840955

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Bayesian Data Analysis, Third Edition by Andrew Gelman,John B. Carlin,Hal S. Stern,David B. Dunson,Aki Vehtari,Donald B. Rubin Pdf

Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.

Author : Rajnish Kumar Misra,Archana Shrivastava,Charu Sijoria
Publisher : Emerald Group Publishing
Page : 217 pages
File Size : 41,7 Mb
Release : 2023-06-27
Category : Business & Economics
ISBN : 9781804555187

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Technology, Management and Business by Rajnish Kumar Misra,Archana Shrivastava,Charu Sijoria Pdf

Advanced Series in Management: Volume 31 offers cutting-edge research from an international range of academics, who engage with the potential opportunities and challenges of digitization in the workplace.

Author : Richard Schwindt
Publisher : Unknown
Page : 236 pages
File Size : 46,9 Mb
Release : 1995
Category : Business education
ISBN : CORNELL:31924073443768

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Management Information Systems and Business Statistics by Richard Schwindt Pdf

Author : Nguyen Ngoc Thach,Vladik Kreinovich,Doan Thanh Ha,Nguyen Duc Trung
Publisher : Springer Nature
Page : 865 pages
File Size : 55,8 Mb
Release : 2022-05-28
Category : Technology & Engineering
ISBN : 9783030986896

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Financial Econometrics: Bayesian Analysis, Quantum Uncertainty, and Related Topics by Nguyen Ngoc Thach,Vladik Kreinovich,Doan Thanh Ha,Nguyen Duc Trung Pdf

This book overviews latest ideas and developments in financial econometrics, with an emphasis on how to best use prior knowledge (e.g., Bayesian way) and how to best use successful data processing techniques from other application areas (e.g., from quantum physics). The book also covers applications to economy-related phenomena ranging from traditionally analyzed phenomena such as manufacturing, food industry, and taxes, to newer-to-analyze phenomena such as cryptocurrencies, influencer marketing, COVID-19 pandemic, financial fraud detection, corruption, and shadow economy. This book will inspire practitioners to learn how to apply state-of-the-art Bayesian, quantum, and related techniques to economic and financial problems and inspire researchers to further improve the existing techniques and come up with new techniques for studying economic and financial phenomena. The book will also be of interest to students interested in latest ideas and results.

Author : Norman Fenton,Martin Neil
Publisher : CRC Press
Page : 516 pages
File Size : 46,5 Mb
Release : 2012-11-07
Category : Business & Economics
ISBN : 9781439809112

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Risk Assessment and Decision Analysis with Bayesian Networks by Norman Fenton,Martin Neil Pdf

Although many Bayesian Network (BN) applications are now in everyday use, BNs have not yet achieved mainstream penetration. Focusing on practical real-world problem solving and model building, as opposed to algorithms and theory, Risk Assessment and Decision Analysis with Bayesian Networks explains how to incorporate knowledge with data to develop and use (Bayesian) causal models of risk that provide powerful insights and better decision making. Provides all tools necessary to build and run realistic Bayesian network models Supplies extensive example models based on real risk assessment problems in a wide range of application domains provided; for example, finance, safety, systems reliability, law, and more Introduces all necessary mathematics, probability, and statistics as needed The book first establishes the basics of probability, risk, and building and using BN models, then goes into the detailed applications. The underlying BN algorithms appear in appendices rather than the main text since there is no need to understand them to build and use BN models. Keeping the body of the text free of intimidating mathematics, the book provides pragmatic advice about model building to ensure models are built efficiently. A dedicated website, www.BayesianRisk.com, contains executable versions of all of the models described, exercises and worked solutions for all chapters, PowerPoint slides, numerous other resources, and a free downloadable copy of the AgenaRisk software.

Author : Jonas Mockus
Publisher : Springer Science & Business Media
Page : 267 pages
File Size : 53,5 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9789400909090

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Bayesian Approach to Global Optimization by Jonas Mockus Pdf

·Et moi ... si j'avait su comment en revcnir. One service mathematics has rendered the je o'y semis point alle.' human race. It has put common sense back Jules Verne where it beloogs. on the topmost shelf next to the dusty canister labelled 'discarded non The series is divergent; therefore we may be sense', able to do something with it. Eric T. BclI O. Heaviside Mathematics is a tool for thought. A highly necessary tool in a world where both feedback and non linearities abound. Similarly, all kinds of parts of mathematics serve as tools for other parts and for other sciences. Applying a simple rewriting rule to the quote on the right above one finds such statements as: 'One service topology has rendered mathematical physics ... '; 'One service logic has rendered com puter science .. .'; 'One service category theory has rendered mathematics .. .'. All arguably true. And all statements obtainable this way form part of the raison d'etre of this series.