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A First Course in Bayesian Statistical Methods
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A self-contained introduction to probability, exchangeability and Bayes' rule provides a theoretical understanding of the applied material.
Numerous examples with R-code that can be run as-is allow the reader to perform the data analyses themselves.
The development of Monte Carlo and Markov chain Monte Carlo methods in the context of data analysis examples provides motivatio ...more
Numerous examples with R-code that can be run as-is allow the reader to perform the data analyses themselves.
The development of Monte Carlo and Markov chain Monte Carlo methods in the context of data analysis examples provides motivatio ...more
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Hardcover, 271 pages
Published
June 1st 2009
by Springer
(first published 2009)
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Reader-friendly intro to Bayesian Statistics.
- We can understand Bayesian statistics first from the Bayes Rule
- Benefit of using Bayes to learn p(theta | data) is good because we can get a distribution of theta. Also for p( data_output | data_input), we also get a distribution of data_outputs, which can represent "uncertainty."
- Then, the marginalization term in the Bayes Rule is really hard to calculate, so Variational Inference (using a q(theta) to model p(theta | data_input, data_output) ) is ...more
- We can understand Bayesian statistics first from the Bayes Rule
- Benefit of using Bayes to learn p(theta | data) is good because we can get a distribution of theta. Also for p( data_output | data_input), we also get a distribution of data_outputs, which can represent "uncertainty."
- Then, the marginalization term in the Bayes Rule is really hard to calculate, so Variational Inference (using a q(theta) to model p(theta | data_input, data_output) ) is ...more
There is so much wrong with this book. God help you if this is the material you have for your first glimpse of Bayesian methods applied to statistics. It redeems itself slightly as I find it useful as a dense reference.
The book reads like an unfinished effort to convert lecture slides and notes into a book format. So many sections read like Powerpoint slides-short and somewhat disconnected from the surrounding material. Many of the subheadings are are quite possibly the vestiges of Powerpoint sl ...more
The book reads like an unfinished effort to convert lecture slides and notes into a book format. So many sections read like Powerpoint slides-short and somewhat disconnected from the surrounding material. Many of the subheadings are are quite possibly the vestiges of Powerpoint sl ...more
I'm still searching for a readable Baysian statistics reference. I bought the digital version thinking that I would be able to use it as a reference, but it appears that it is not my ideal reference book. It is difficult to read and equally difficult to look things up in this book.
...more
It was long ago when I have read this book. It was very nice introduction with a lot of exercises. But I remember there was a lot of mistakes in it, even in the equations. I think the author have a list of those on his website.
Great, introduction to Bayesian analysis and R.
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