Bayesian Methods for Statistical Analysis

Bayesian Methods for Statistical Analysis

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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 m...

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Bibliographic Details
Main Author: Puza, Borek (auth)
Format: Electronic Book Chapter
Language:English
Published: ANU Press 2015
Subjects:
Mathematics
Probability & statistics
Bayesian inference
statistics
mathematics
bayesian inference
probability
Algorithm
Confidence interval
Histogram
Monte Carlo method
Posterior probability
Sampling (statistics)
WinBUGS
Online Access:DOAB: download the publication
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Summary: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.
ISBN:OAPEN_611011
9781921934254
Access:Open Access

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