This is a collection of practical exercises from old courses, mostly my old module in “Bayesian Computation”. Unless otherwise stated, references to lecture notes refer to the “Bayesian Compu-tation ” notes. The exercises use R and BUGS. Both R and BUGS are available in the School of Mathematics and Statistics. You can download R from the Web, at no cost. There are versions for several operating systems including Unix, Mac OS and Windows. For further information see the following web site
Solutions des exercices proposés dans cet ouvrage librement accessibles à http://fr.arxiv.org/abs/10...
Background: Many recent statistical applications involve inference under complex models, where it is...
While Robert and Rousseau (2010) addressed the foundational aspects of Bayesian analysis, the curren...
Preliminary Version This material is used as a reference for the computer exercises of the Bayesian ...
There is an explosion of interest in Bayesian statistics, primarily because recently created computa...
This Bayesian modeling book is intended for practitioners and applied statisticians looking for a se...
There has been a dramatic growth in the development and application of Bayesian inferential methods....
118+vii pages, 21 figures, 152 solutionsThis solution manual contains the unabridged and original so...
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...
A new book in the Econometric Exercises series, this volume contains questions and answers to provid...
Introduction: Probability and ParametersProbabilityProbability distributionsCalculating properties o...
Supplementary code to pyABC: Efficient and robust easy-to-use approximate Bayesian computation, Schä...
Tutorial on approximate Bayesian computation. The objective of the tutorial is to provide an insight...
In this video, Dr Gabriel Katz talks about the basics of Bayesian computation, working through a ser...
Solutions des exercices proposés dans cet ouvrage librement accessibles à http://fr.arxiv.org/abs/10...
Background: Many recent statistical applications involve inference under complex models, where it is...
While Robert and Rousseau (2010) addressed the foundational aspects of Bayesian analysis, the curren...
Preliminary Version This material is used as a reference for the computer exercises of the Bayesian ...
There is an explosion of interest in Bayesian statistics, primarily because recently created computa...
This Bayesian modeling book is intended for practitioners and applied statisticians looking for a se...
There has been a dramatic growth in the development and application of Bayesian inferential methods....
118+vii pages, 21 figures, 152 solutionsThis solution manual contains the unabridged and original so...
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...
A new book in the Econometric Exercises series, this volume contains questions and answers to provid...
Introduction: Probability and ParametersProbabilityProbability distributionsCalculating properties o...
Supplementary code to pyABC: Efficient and robust easy-to-use approximate Bayesian computation, Schä...
Tutorial on approximate Bayesian computation. The objective of the tutorial is to provide an insight...
In this video, Dr Gabriel Katz talks about the basics of Bayesian computation, working through a ser...
Solutions des exercices proposés dans cet ouvrage librement accessibles à http://fr.arxiv.org/abs/10...
Background: Many recent statistical applications involve inference under complex models, where it is...
While Robert and Rousseau (2010) addressed the foundational aspects of Bayesian analysis, the curren...