Current Trends in Bayesian Methodology with Applications

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Publisher : CRC Press
ISBN 13 : 1482235129
Total Pages : 674 pages
Book Rating : 4.4/5 (822 download)

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Book Synopsis Current Trends in Bayesian Methodology with Applications by : Satyanshu K. Upadhyay

Download or read book Current Trends in Bayesian Methodology with Applications written by Satyanshu K. Upadhyay and published by CRC Press. This book was released on 2015-05-21 with total page 674 pages. Available in PDF, EPUB and Kindle. Book excerpt: Collecting Bayesian material scattered throughout the literature, Current Trends in Bayesian Methodology with Applications examines the latest methodological and applied aspects of Bayesian statistics. The book covers biostatistics, econometrics, reliability and risk analysis, spatial statistics, image analysis, shape analysis, Bayesian computation, clustering, uncertainty assessment, high-energy astrophysics, neural networking, fuzzy information, objective Bayesian methodologies, empirical Bayes methods, small area estimation, and many more topics. Each chapter is self-contained and focuses on a Bayesian methodology. It gives an overview of the area, presents theoretical insights, and emphasizes applications through motivating examples. This book reflects the diversity of Bayesian analysis, from novel Bayesian methodology, such as nonignorable response and factor analysis, to state-of-the-art applications in economics, astrophysics, biomedicine, oceanography, and other areas. It guides readers in using Bayesian techniques for a range of statistical analyses.

New Developments in the Applications of Bayesian Methods

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Publisher : North-Holland
ISBN 13 :
Total Pages : 420 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis New Developments in the Applications of Bayesian Methods by : Ahmet Aykaç

Download or read book New Developments in the Applications of Bayesian Methods written by Ahmet Aykaç and published by North-Holland. This book was released on 1977 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt:

New Development in the Applications of Bayesian Methods

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Publisher :
ISBN 13 :
Total Pages : 385 pages
Book Rating : 4.:/5 (11 download)

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Book Synopsis New Development in the Applications of Bayesian Methods by :

Download or read book New Development in the Applications of Bayesian Methods written by and published by . This book was released on 1977 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Bayesian Applications in Pharmaceutical Development

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Publisher : CRC Press
ISBN 13 : 1351584170
Total Pages : 532 pages
Book Rating : 4.3/5 (515 download)

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Book Synopsis Bayesian Applications in Pharmaceutical Development by : Mani Lakshminarayanan

Download or read book Bayesian Applications in Pharmaceutical Development written by Mani Lakshminarayanan and published by CRC Press. This book was released on 2019-11-07 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt: The cost for bringing new medicine from discovery to market has nearly doubled in the last decade and has now reached $2.6 billion. There is an urgent need to make drug development less time-consuming and less costly. Innovative trial designs/ analyses such as the Bayesian approach are essential to meet this need. This book will be the first to provide comprehensive coverage of Bayesian applications across the span of drug development, from discovery, to clinical trial, to manufacturing with practical examples. This book will have a wide appeal to statisticians, scientists, and physicians working in drug development who are motivated to accelerate and streamline the drug development process, as well as students who aspire to work in this field. The advantages of this book are: Provides motivating, worked, practical case examples with easy to grasp models, technical details, and computational codes to run the analyses Balances practical examples with best practices on trial simulation and reporting, as well as regulatory perspectives Chapters written by authors who are individual contributors in their respective topics Dr. Mani Lakshminarayanan is a researcher and statistical consultant with more than 30 years of experience in the pharmaceutical industry. He has published over 50 articles, technical reports, and book chapters besides serving as a referee for several journals. He has a PhD in Statistics from Southern Methodist University, Dallas, Texas and is a Fellow of the American Statistical Association. Dr. Fanni Natanegara has over 15 years of pharmaceutical experience and is currently Principal Research Scientist and Group Leader for the Early Phase Neuroscience Statistics team at Eli Lilly and Company. She played a key role in the Advanced Analytics team to provide Bayesian education and statistical consultation at Eli Lilly. Dr. Natanegara is the chair of the cross industry-regulatory-academic DIA BSWG to ensure that Bayesian methods are appropriately utilized for design and analysis throughout the drug-development process.

NEW DEVELOPMENTS IN THE APPLICATIONS OF BAYESIAN METHODS- PROCEEDINGS- 1ST EUROPEAN CONFERENCE- CENTRE EUROPEEN D'EDUCATION PERMANENTE- INSTITUT EUROPEEN D'ADMINISTRATION DES AFFAIRES.

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Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (846 download)

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Book Synopsis NEW DEVELOPMENTS IN THE APPLICATIONS OF BAYESIAN METHODS- PROCEEDINGS- 1ST EUROPEAN CONFERENCE- CENTRE EUROPEEN D'EDUCATION PERMANENTE- INSTITUT EUROPEEN D'ADMINISTRATION DES AFFAIRES. by :

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Advancements in Bayesian Methods and Implementations

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Publisher : Academic Press
ISBN 13 : 0323952690
Total Pages : 322 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Advancements in Bayesian Methods and Implementations by :

Download or read book Advancements in Bayesian Methods and Implementations written by and published by Academic Press. This book was released on 2022-10-06 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Bayesian Methods in Pharmaceutical Research

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Publisher : CRC Press
ISBN 13 : 1351718673
Total Pages : 547 pages
Book Rating : 4.3/5 (517 download)

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Book Synopsis Bayesian Methods in Pharmaceutical Research by : Emmanuel Lesaffre

Download or read book Bayesian Methods in Pharmaceutical Research written by Emmanuel Lesaffre and published by CRC Press. This book was released on 2020-04-15 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the early 2000s, there has been increasing interest within the pharmaceutical industry in the application of Bayesian methods at various stages of the research, development, manufacturing, and health economic evaluation of new health care interventions. In 2010, the first Applied Bayesian Biostatistics conference was held, with the primary objective to stimulate the practical implementation of Bayesian statistics, and to promote the added-value for accelerating the discovery and the delivery of new cures to patients. This book is a synthesis of the conferences and debates, providing an overview of Bayesian methods applied to nearly all stages of research and development, from early discovery to portfolio management. It highlights the value associated with sharing a vision with the regulatory authorities, academia, and pharmaceutical industry, with a view to setting up a common strategy for the appropriate use of Bayesian statistics for the benefit of patients. The book covers: Theory, methods, applications, and computing Bayesian biostatistics for clinical innovative designs Adding value with Real World Evidence Opportunities for rare, orphan diseases, and pediatric development Applied Bayesian biostatistics in manufacturing Decision making and Portfolio management Regulatory perspective and public health policies Statisticians and data scientists involved in the research, development, and approval of new cures will be inspired by the possible applications of Bayesian methods covered in the book. The methods, applications, and computational guidance will enable the reader to apply Bayesian methods in their own pharmaceutical research.

Bayesian Applications in Pharmaceutical Development

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Publisher : CRC Press
ISBN 13 : 1351584162
Total Pages : 453 pages
Book Rating : 4.3/5 (515 download)

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Book Synopsis Bayesian Applications in Pharmaceutical Development by : Mani Lakshminarayanan

Download or read book Bayesian Applications in Pharmaceutical Development written by Mani Lakshminarayanan and published by CRC Press. This book was released on 2019-11-07 with total page 453 pages. Available in PDF, EPUB and Kindle. Book excerpt: The cost for bringing new medicine from discovery to market has nearly doubled in the last decade and has now reached $2.6 billion. There is an urgent need to make drug development less time-consuming and less costly. Innovative trial designs/ analyses such as the Bayesian approach are essential to meet this need. This book will be the first to provide comprehensive coverage of Bayesian applications across the span of drug development, from discovery, to clinical trial, to manufacturing with practical examples. This book will have a wide appeal to statisticians, scientists, and physicians working in drug development who are motivated to accelerate and streamline the drug development process, as well as students who aspire to work in this field. The advantages of this book are: Provides motivating, worked, practical case examples with easy to grasp models, technical details, and computational codes to run the analyses Balances practical examples with best practices on trial simulation and reporting, as well as regulatory perspectives Chapters written by authors who are individual contributors in their respective topics Dr. Mani Lakshminarayanan is a researcher and statistical consultant with more than 30 years of experience in the pharmaceutical industry. He has published over 50 articles, technical reports, and book chapters besides serving as a referee for several journals. He has a PhD in Statistics from Southern Methodist University, Dallas, Texas and is a Fellow of the American Statistical Association. Dr. Fanni Natanegara has over 15 years of pharmaceutical experience and is currently Principal Research Scientist and Group Leader for the Early Phase Neuroscience Statistics team at Eli Lilly and Company. She played a key role in the Advanced Analytics team to provide Bayesian education and statistical consultation at Eli Lilly. Dr. Natanegara is the chair of the cross industry-regulatory-academic DIA BSWG to ensure that Bayesian methods are appropriately utilized for design and analysis throughout the drug-development process.

Bayesian Theory and Applications

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Author :
Publisher : OUP Oxford
ISBN 13 : 0191647004
Total Pages : 717 pages
Book Rating : 4.1/5 (916 download)

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Book Synopsis Bayesian Theory and Applications by : Paul Damien

Download or read book Bayesian Theory and Applications written by Paul Damien and published by OUP Oxford. This book was released on 2013-01-24 with total page 717 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of hierarchical models and Markov chain Monte Carlo (MCMC) techniques forms one of the most profound advances in Bayesian analysis since the 1970s and provides the basis for advances in virtually all areas of applied and theoretical Bayesian statistics. This volume guides the reader along a statistical journey that begins with the basic structure of Bayesian theory, and then provides details on most of the past and present advances in this field. The book has a unique format. There is an explanatory chapter devoted to each conceptual advance followed by journal-style chapters that provide applications or further advances on the concept. Thus, the volume is both a textbook and a compendium of papers covering a vast range of topics. It is appropriate for a well-informed novice interested in understanding the basic approach, methods and recent applications. Because of its advanced chapters and recent work, it is also appropriate for a more mature reader interested in recent applications and developments, and who may be looking for ideas that could spawn new research. Hence, the audience for this unique book would likely include academicians/practitioners, and could likely be required reading for undergraduate and graduate students in statistics, medicine, engineering, scientific computation, business, psychology, bio-informatics, computational physics, graphical models, neural networks, geosciences, and public policy. The book honours the contributions of Sir Adrian F. M. Smith, one of the seminal Bayesian researchers, with his papers on hierarchical models, sequential Monte Carlo, and Markov chain Monte Carlo and his mentoring of numerous graduate students -the chapters are authored by prominent statisticians influenced by him. Bayesian Theory and Applications should serve the dual purpose of a reference book, and a textbook in Bayesian Statistics.

New developments in the applications of Bayesian methods

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Publisher :
ISBN 13 :
Total Pages : 385 pages
Book Rating : 4.:/5 (469 download)

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Book Synopsis New developments in the applications of Bayesian methods by : Ahmet Aykac

Download or read book New developments in the applications of Bayesian methods written by Ahmet Aykac and published by . This book was released on 1977 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt:

New developments in the applications of Bayesian methods: proceedings of the first European conference sponsored by the Centre européen d'éducation permanente (CEDEP) and the Institute européen d'administration des affaires (INSED) June 1976

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Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (933 download)

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Book Synopsis New developments in the applications of Bayesian methods: proceedings of the first European conference sponsored by the Centre européen d'éducation permanente (CEDEP) and the Institute européen d'administration des affaires (INSED) June 1976 by :

Download or read book New developments in the applications of Bayesian methods: proceedings of the first European conference sponsored by the Centre européen d'éducation permanente (CEDEP) and the Institute européen d'administration des affaires (INSED) June 1976 written by and published by . This book was released on 1979 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

New Developments in the Applications of Bayesian Methods

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Publisher :
ISBN 13 :
Total Pages : 385 pages
Book Rating : 4.:/5 (473 download)

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Book Synopsis New Developments in the Applications of Bayesian Methods by : Centre européen d'education permanente (Fontainebleau)

Download or read book New Developments in the Applications of Bayesian Methods written by Centre européen d'education permanente (Fontainebleau) and published by . This book was released on 1977 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Bayesian Statistics 9

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Publisher : Oxford University Press
ISBN 13 : 0191627852
Total Pages : pages
Book Rating : 4.1/5 (916 download)

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Book Synopsis Bayesian Statistics 9 by : José M. Bernardo

Download or read book Bayesian Statistics 9 written by José M. Bernardo and published by Oxford University Press. This book was released on 2011-10-06 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The Valencia International Meetings on Bayesian Statistics - established in 1979 and held every four years - have been the forum for a definitive overview of current concerns and activities in Bayesian statistics. These are the edited Proceedings of the Ninth meeting, and contain the invited papers each followed by their discussion and a rejoinder by the authors(s). In the tradition of the earlier editions, this encompasses an enormous range of theoretical and applied research, high lighting the breadth, vitality and impact of Bayesian thinking in interdisciplinary research across many fields as well as the corresponding growth and vitality of core theory and methodology. The Valencia 9 invited papers cover a broad range of topics, including foundational and core theoretical issues in statistics, the continued development of new and refined computational methods for complex Bayesian modelling, substantive applications of flexible Bayesian modelling, and new developments in the theory and methodology of graphical modelling. They also describe advances in methodology for specific applied fields, including financial econometrics and portfolio decision making, public policy applications for drug surveillance, studies in the physical and environmental sciences, astronomy and astrophysics, climate change studies, molecular biosciences, statistical genetics or stochastic dynamic networks in systems biology.

Bayesian Methods for Hackers

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Publisher : Addison-Wesley Professional
ISBN 13 : 0133902927
Total Pages : 551 pages
Book Rating : 4.1/5 (339 download)

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Book Synopsis Bayesian Methods for Hackers by : Cameron Davidson-Pilon

Download or read book Bayesian Methods for Hackers written by Cameron Davidson-Pilon and published by Addison-Wesley Professional. This book was released on 2015-09-30 with total page 551 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master Bayesian Inference through Practical Examples and Computation–Without Advanced Mathematical Analysis Bayesian methods of inference are deeply natural and extremely powerful. However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice–freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You’ll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you’ve mastered these techniques, you’ll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes • Learning the Bayesian “state of mind” and its practical implications • Understanding how computers perform Bayesian inference • Using the PyMC Python library to program Bayesian analyses • Building and debugging models with PyMC • Testing your model’s “goodness of fit” • Opening the “black box” of the Markov Chain Monte Carlo algorithm to see how and why it works • Leveraging the power of the “Law of Large Numbers” • Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning • Using loss functions to measure an estimate’s weaknesses based on your goals and desired outcomes • Selecting appropriate priors and understanding how their influence changes with dataset size • Overcoming the “exploration versus exploitation” dilemma: deciding when “pretty good” is good enough • Using Bayesian inference to improve A/B testing • Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify.

Bayesian Methods for Structural Dynamics and Civil Engineering

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Publisher : John Wiley & Sons
ISBN 13 : 9780470824559
Total Pages : 320 pages
Book Rating : 4.8/5 (245 download)

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Book Synopsis Bayesian Methods for Structural Dynamics and Civil Engineering by : Ka-Veng Yuen

Download or read book Bayesian Methods for Structural Dynamics and Civil Engineering written by Ka-Veng Yuen and published by John Wiley & Sons. This book was released on 2010-02-22 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian methods are a powerful tool in many areas of science and engineering, especially statistical physics, medical sciences, electrical engineering, and information sciences. They are also ideal for civil engineering applications, given the numerous types of modeling and parametric uncertainty in civil engineering problems. For example, earthquake ground motion cannot be predetermined at the structural design stage. Complete wind pressure profiles are difficult to measure under operating conditions. Material properties can be difficult to determine to a very precise level – especially concrete, rock, and soil. For air quality prediction, it is difficult to measure the hourly/daily pollutants generated by cars and factories within the area of concern. It is also difficult to obtain the updated air quality information of the surrounding cities. Furthermore, the meteorological conditions of the day for prediction are also uncertain. These are just some of the civil engineering examples to which Bayesian probabilistic methods are applicable. Familiarizes readers with the latest developments in the field Includes identification problems for both dynamic and static systems Addresses challenging civil engineering problems such as modal/model updating Presents methods applicable to mechanical and aerospace engineering Gives engineers and engineering students a concrete sense of implementation Covers real-world case studies in civil engineering and beyond, such as: structural health monitoring seismic attenuation finite-element model updating hydraulic jump artificial neural network for damage detection air quality prediction Includes other insightful daily-life examples Companion website with MATLAB code downloads for independent practice Written by a leading expert in the use of Bayesian methods for civil engineering problems This book is ideal for researchers and graduate students in civil and mechanical engineering or applied probability and statistics. Practicing engineers interested in the application of statistical methods to solve engineering problems will also find this to be a valuable text. MATLAB code and lecture materials for instructors available at http://www.wiley.com/go/yuen

Bayesian Analysis with R for Drug Development

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Publisher : CRC Press
ISBN 13 : 1351585940
Total Pages : 310 pages
Book Rating : 4.3/5 (515 download)

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Book Synopsis Bayesian Analysis with R for Drug Development by : Harry Yang

Download or read book Bayesian Analysis with R for Drug Development written by Harry Yang and published by CRC Press. This book was released on 2019-06-26 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Drug development is an iterative process. The recent publications of regulatory guidelines further entail a lifecycle approach. Blending data from disparate sources, the Bayesian approach provides a flexible framework for drug development. Despite its advantages, the uptake of Bayesian methodologies is lagging behind in the field of pharmaceutical development. Written specifically for pharmaceutical practitioners, Bayesian Analysis with R for Drug Development: Concepts, Algorithms, and Case Studies, describes a wide range of Bayesian applications to problems throughout pre-clinical, clinical, and Chemistry, Manufacturing, and Control (CMC) development. Authored by two seasoned statisticians in the pharmaceutical industry, the book provides detailed Bayesian solutions to a broad array of pharmaceutical problems. Features Provides a single source of information on Bayesian statistics for drug development Covers a wide spectrum of pre-clinical, clinical, and CMC topics Demonstrates proper Bayesian applications using real-life examples Includes easy-to-follow R code with Bayesian Markov Chain Monte Carlo performed in both JAGS and Stan Bayesian software platforms Offers sufficient background for each problem and detailed description of solutions suitable for practitioners with limited Bayesian knowledge Harry Yang, Ph.D., is Senior Director and Head of Statistical Sciences at AstraZeneca. He has 24 years of experience across all aspects of drug research and development and extensive global regulatory experiences. He has published 6 statistical books, 15 book chapters, and over 90 peer-reviewed papers on diverse scientific and statistical subjects, including 15 joint statistical works with Dr. Novick. He is a frequent invited speaker at national and international conferences. He also developed statistical courses and conducted training at the FDA and USP as well as Peking University. Steven Novick, Ph.D., is Director of Statistical Sciences at AstraZeneca. He has extensively contributed statistical methods to the biopharmaceutical literature. Novick is a skilled Bayesian computer programmer and is frequently invited to speak at conferences, having developed and taught courses in several areas, including drug-combination analysis and Bayesian methods in clinical areas. Novick served on IPAC-RS and has chaired several national statistical conferences.

Bayesian Inference in the Social Sciences

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Publisher : John Wiley & Sons
ISBN 13 : 1118771125
Total Pages : 266 pages
Book Rating : 4.1/5 (187 download)

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Book Synopsis Bayesian Inference in the Social Sciences by : Ivan Jeliazkov

Download or read book Bayesian Inference in the Social Sciences written by Ivan Jeliazkov and published by John Wiley & Sons. This book was released on 2014-11-04 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents new models, methods, and techniques and considers important real-world applications in political science, sociology, economics, marketing, and finance Emphasizing interdisciplinary coverage, Bayesian Inference in the Social Sciences builds upon the recent growth in Bayesian methodology and examines an array of topics in model formulation, estimation, and applications. The book presents recent and trending developments in a diverse, yet closely integrated, set of research topics within the social sciences and facilitates the transmission of new ideas and methodology across disciplines while maintaining manageability, coherence, and a clear focus. Bayesian Inference in the Social Sciences features innovative methodology and novel applications in addition to new theoretical developments and modeling approaches, including the formulation and analysis of models with partial observability, sample selection, and incomplete data. Additional areas of inquiry include a Bayesian derivation of empirical likelihood and method of moment estimators, and the analysis of treatment effect models with endogeneity. The book emphasizes practical implementation, reviews and extends estimation algorithms, and examines innovative applications in a multitude of fields. Time series techniques and algorithms are discussed for stochastic volatility, dynamic factor, and time-varying parameter models. Additional features include: Real-world applications and case studies that highlight asset pricing under fat-tailed distributions, price indifference modeling and market segmentation, analysis of dynamic networks, ethnic minorities and civil war, school choice effects, and business cycles and macroeconomic performance State-of-the-art computational tools and Markov chain Monte Carlo algorithms with related materials available via the book’s supplemental website Interdisciplinary coverage from well-known international scholars and practitioners Bayesian Inference in the Social Sciences is an ideal reference for researchers in economics, political science, sociology, and business as well as an excellent resource for academic, government, and regulation agencies. The book is also useful for graduate-level courses in applied econometrics, statistics, mathematical modeling and simulation, numerical methods, computational analysis, and the social sciences.