There is an explosion of interest in Bayesian statistics, primarily because recently created computational methods have finally made Bayesian analysis obtainable to a wide audience. Doing Bayesian Data Analysis, A Tutorial Introduction with R and BUGS provides an accessible approach to Bayesian data analysis, as material is explained clearly with concrete examples. The book begins with the basics, including essential concepts of probability and random sampling, and gradually progresses to advanced hierarchical modeling methods for realistic data. The text delivers comprehensive coverage of al
A hands-on introduction to the principles of Bayesian modeling using WinBUGS Bayesian Modeling Using...
The Bayesian researcher should know the basic ideas underlying Bayesian methodology and the computat...
This is a 20 page chapter for the upcoming Handbook of Statistical Systems Biology (D. Balding, M. S...
This Bayesian modeling book provides a self-contained entry to computational Bayesian statistics. Fo...
International audienceThis Bayesian modeling book provides a self-contained entry to computational B...
Engaging and accessible, this book teaches readers how to use inferential statistical thinking to ch...
In this video, Andrei introduces a series of videos looking at Bayesian data analysis. These will of...
This Bayesian modeling book is intended for practitioners and applied statisticians looking for a se...
Introduction: Probability and ParametersProbabilityProbability distributionsCalculating properties o...
There has been a dramatic growth in the development and application of Bayesian inferential methods....
There is a strong upsurge in the use of Bayesian methods in applied statistical analysis, yet most i...
Bayesian statistics is an approach to data analysis based on Bayes’ theorem, where available knowled...
Tutorial on approximate Bayesian computation. The objective of the tutorial is to provide an insight...
This is a chapter for the book "Bayesian Methods and Expert Elicitation" edited by Klaus Bocker, 23 ...
Bayesian methods for statistical analysis is a book on statistical methods for analysing a wide vari...
A hands-on introduction to the principles of Bayesian modeling using WinBUGS Bayesian Modeling Using...
The Bayesian researcher should know the basic ideas underlying Bayesian methodology and the computat...
This is a 20 page chapter for the upcoming Handbook of Statistical Systems Biology (D. Balding, M. S...
This Bayesian modeling book provides a self-contained entry to computational Bayesian statistics. Fo...
International audienceThis Bayesian modeling book provides a self-contained entry to computational B...
Engaging and accessible, this book teaches readers how to use inferential statistical thinking to ch...
In this video, Andrei introduces a series of videos looking at Bayesian data analysis. These will of...
This Bayesian modeling book is intended for practitioners and applied statisticians looking for a se...
Introduction: Probability and ParametersProbabilityProbability distributionsCalculating properties o...
There has been a dramatic growth in the development and application of Bayesian inferential methods....
There is a strong upsurge in the use of Bayesian methods in applied statistical analysis, yet most i...
Bayesian statistics is an approach to data analysis based on Bayes’ theorem, where available knowled...
Tutorial on approximate Bayesian computation. The objective of the tutorial is to provide an insight...
This is a chapter for the book "Bayesian Methods and Expert Elicitation" edited by Klaus Bocker, 23 ...
Bayesian methods for statistical analysis is a book on statistical methods for analysing a wide vari...
A hands-on introduction to the principles of Bayesian modeling using WinBUGS Bayesian Modeling Using...
The Bayesian researcher should know the basic ideas underlying Bayesian methodology and the computat...
This is a 20 page chapter for the upcoming Handbook of Statistical Systems Biology (D. Balding, M. S...