George E. P. Box Bayesian Inference in Statistical Analysis
Купить за 18327.81 RUR
Its main objective is to examine the application and relevance of Bayes' theorem to problems that arise in scientific investigation in which inferences must be made regarding parameter values about which little is known a priori. Begins with a discussion of some important general aspects of the
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Группа авторов Bayesian Inference in the Social Sciences
Купить за 12400.05 RUR
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
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Bayesian Inference and Machine Learning Tutorial
Купить за 2650 RUR
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Franco Taroni Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science
Купить за 9553.8 RUR
"This book should have a place on the bookshelf of every forensic scientist who cares about the science of evidence interpretation" Dr. Ian Evett, Principal Forensic Services Ltd, London, UK Continuing developments in science and technology mean that the amounts of information forensic scientists
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William M. Bolstad Introduction to Bayesian Statistics
Купить за 13566.76 RUR
"…this edition is useful and effective in teaching Bayesian inference at both elementary and intermediate levels. It is a well-written book on elementary Bayesian inference, and the material is easily accessible. It is both concise and timely, and provides a good collection of overviews and reviews
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George E. P. Box An Accidental Statistician
Купить за 3650.89 RUR
Celebrating the life of an admired pioneer in statistics In this captivating and inspiring memoir, world-renowned statistician George E. P. Box offers a firsthand account of his life and statistical work. Writing in an engaging, charming style, Dr. Box reveals the unlikely events that led him to a
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Ali Nayfeh H. Perturbation Methods
Купить за 11528.94 RUR
The Wiley Classics Library consists of selected books that have become recognized classics in their respective fields. With these new unabridged and inexpensive editions, Wiley hopes to extend the life of these important works by making them available to future generations of mathematicians and
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Andrew Gelman Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives
Купить за 13393.2 RUR
This book brings together a collection of articles on statistical methods relating to missing data analysis, including multiple imputation, propensity scores, instrumental variables, and Bayesian inference. Covering new research topics and real-world examples which do not feature in many standard
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Myles Hollander Statistics
Купить за 19610.15 RUR
The Wiley Classics Library consists of selected books that have become recognized classics in their respective fields. With these new unabridged and inexpensive editions, Wiley hopes to extend the life of these important works by making them available to future generations of mathematicians and
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George E. P. Box Statistical Control by Monitoring and Adjustment
Купить за 12377.16 RUR
Praise for the First Edition «This book . . . is a significant addition to the literature on statistical practice . . . should be of considerable interest to those interested in these topics.»—International Journal of Forecasting Recent research has shown that monitoring techniques alone are
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George E. P. Box Response Surfaces, Mixtures, and Ridge Analyses
Купить за 17412.88 RUR
The authority on building empirical models and the fitting of such surfaces to data—completely updated and revised Revising and updating a volume that represents the essential source on building empirical models, George Box and Norman Draper—renowned authorities in this field—continue to set the
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Ioannis Ntzoufras Bayesian Modeling Using WinBUGS
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A hands-on introduction to the principles of Bayesian modeling using WinBUGS Bayesian Modeling Using WinBUGS provides an easily accessible introduction to the use of WinBUGS programming techniques in a variety of Bayesian modeling settings. The author provides an accessible treatment of the topic,
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