Bayesian methods for statistical analysis is a book on statistical methods for analysing a wide variety of data. The book consists of 12 chapters, starting with basic concepts and covering numerous topics, including Bayesian estimation, decision theory, prediction, hypothesis testing, hierarchical models, Markov chain Monte Carlo methods, finite population inference, biased sampling and nonignorable nonresponse. The book contains many exercises, all with worked solutions, including complete computer code. It is suitable for self-study or a semester-long course, with three hours of lectures and one tutorial per week for 13 weeks
The Bayesian approach allows an intuitive way to derive the methods of statistics. Probability is de...
Chapter written for the Handbook of Research Methods and Applications on Empirical Macroeconomics, e...
This Bayesian modeling book is intended for practitioners and applied statisticians looking for a se...
This chapter provides a general overview of Bayesian statistical methods. Topics include the notion ...
This is a chapter for the book "Bayesian Methods and Expert Elicitation" edited by Klaus Bocker, 23 ...
Approaches for statistical inference Introduction Motivating Vignettes Defining the Approaches ...
Bayesian methods for statistical analysis is a book on statistical methods for analysing a wide vari...
Since 1990, Bayesian statistical methods have undergone major advances, both in estimation technique...
A new book in the Econometric Exercises series, this volume contains questions and answers to provid...
There is a strong upsurge in the use of Bayesian methods in applied statistical analysis, yet most i...
Researchers in many fields are increasingly finding the Bayesian approach to statistics to be an att...
This is a 20 page chapter for the upcoming Handbook of Statistical Systems Biology (D. Balding, M. S...
This book describes how Bayesian methods work. Its primary aim is to demystify them, and to show rea...
This chapter provides a overview of Bayesian inference, mostly emphasising that it is a universal me...
The Bayesian researcher should know the basic ideas underlying Bayesian methodology and the computat...
The Bayesian approach allows an intuitive way to derive the methods of statistics. Probability is de...
Chapter written for the Handbook of Research Methods and Applications on Empirical Macroeconomics, e...
This Bayesian modeling book is intended for practitioners and applied statisticians looking for a se...
This chapter provides a general overview of Bayesian statistical methods. Topics include the notion ...
This is a chapter for the book "Bayesian Methods and Expert Elicitation" edited by Klaus Bocker, 23 ...
Approaches for statistical inference Introduction Motivating Vignettes Defining the Approaches ...
Bayesian methods for statistical analysis is a book on statistical methods for analysing a wide vari...
Since 1990, Bayesian statistical methods have undergone major advances, both in estimation technique...
A new book in the Econometric Exercises series, this volume contains questions and answers to provid...
There is a strong upsurge in the use of Bayesian methods in applied statistical analysis, yet most i...
Researchers in many fields are increasingly finding the Bayesian approach to statistics to be an att...
This is a 20 page chapter for the upcoming Handbook of Statistical Systems Biology (D. Balding, M. S...
This book describes how Bayesian methods work. Its primary aim is to demystify them, and to show rea...
This chapter provides a overview of Bayesian inference, mostly emphasising that it is a universal me...
The Bayesian researcher should know the basic ideas underlying Bayesian methodology and the computat...
The Bayesian approach allows an intuitive way to derive the methods of statistics. Probability is de...
Chapter written for the Handbook of Research Methods and Applications on Empirical Macroeconomics, e...
This Bayesian modeling book is intended for practitioners and applied statisticians looking for a se...