Winner of the 2016 De Groot Prize from the International Society for Bayesian Analysis 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 rese... Lees meer.

Help your future genius become the smartest baby in the room by introducing them to Bayesian probability with the next installment of the Baby University board book series. Fans of Chris Ferrie s Rocket Science for Babies Astrophysics for Babies and 8 Little Plan... Lees meer.

Without sacrificing technical integrity for the sake of simplicity the author draws upon accessible student-friendly language to provide approachable instruction perfectly aimed at statistics and Bayesian newcomers.... Lees meer.

A fun guide to learning Bayesian statistics and probability through unusual and illustrative examples. Bayesian Statistics the Fun Way gets you understanding the theory behind data analysis without making you slog through a load of dry concepts first - with no progra... Lees meer.

Doing Bayesian Data Analysis. A Tutorial with R JAGS and Stan Second Edition provides an accessible approach for conducting Bayesian data analysis as material is explained clearly with concrete examples. Included are step-by-step instructions on how to carry out B... Lees meer.

This textbook explains the basic ideas of subjective probability and shows how subjective probabilities must obey the usual rules of probability to ensure coherency. It defines the likelihood function prior distributions and posterior distributions. It explains how pos... Lees meer.

This book provides an authoritative account of Bayesian methodology from its most basic elements to its practical implementations with an emphasis on healthcare techniques. Contains introductory explanations of Bayesian principles common to all areas. The growth... Lees meer.

This is an entry-level book on Bayesian statistics written in a casual and conversational tone. The authors walk a reader through many sample problems step-by-step to provide those with little background in math or statistics with the vocabulary notation and understa... Lees meer.

This dissertation contains three topics using the Bayesian paradigm for statistical inference. The first topic is related to Bayesian sample size determination with a misclassified prevalence variable when two possibly dependent diagnostic tests are used for estimation.... Lees meer.

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Since the first edition of this book published Bayesian networks have become even more important for applications in a vast array of fields. This second edition includes new material on influence diagrams learning from data value of information cybersecurity debunk... Lees meer.

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 Man... Lees meer.

In this book the authors describe the principles and methods behind probabilistic forecasting and Bayesian data assimilation. Instead of focusing on particular application areas the authors adopt a general dynamical systems approach with a profusion of low-dimensiona... Lees meer.

Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applications including search engines DNA sequencing stock market analysis and robot locomotion and their use is s... Lees meer.

Fun guide to learning Bayesian statistics and probability through unusual and illustrative examples. Probability and statistics are increasingly important in a huge range of professions. But many people use data in ways they don t even understand meaning they aren t ge... Lees meer.