Ebook R Tutorial with Bayesian Statistics Using OpenBUGS, by Chi Yau
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R Tutorial with Bayesian Statistics Using OpenBUGS, by Chi Yau
Ebook R Tutorial with Bayesian Statistics Using OpenBUGS, by Chi Yau
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This text provides R tutorials on statistics, including hypothesis testing, ANOVA and linear regression. It fulfills popular demands by users of r-tutor.com for exercise solutions and offline access.
Part III of the text is about Bayesian statistics. It begins with closed analytic solutions and basic BUGS models for simple examples. Then it covers OpenBUGS for Bayesian ANOVA and regression analysis. Finally, it shows how to build more complex Bayesian models and demonstrates CODA for Markov Chain Monte Carlo (MCMC) convergence.
The last part of this text discusses advanced GPU computing in R using the RPUDPLUS package. Topics include hierarchical clustering, Kendall's tau, support vector machines and Bayesian classification. It illustrates the importance of High Performance Computing (HPC) in the future of statistics. The text concludes with a new section on hierarchical multinomial logit model for marketing research.
- Sales Rank: #184451 in eBooks
- Published on: 2013-09-17
- Released on: 2013-09-17
- Format: Kindle eBook
Most helpful customer reviews
13 of 14 people found the following review helpful.
Good value, good reference, not recommended for learning R or statistics
By Skelshy
I've recently done the free coursera data science classes, which I supplemented with books and online resources learning both statistics and R.
In this book, I appreciated I comes at a very reasonable price. Some of the statistics textbooks cost as much as $150. There is also a lot of ground covered in this book. The individual sections are fairly concise and cover a single scenarios with two examples. which I found very similar.
I think there are a number of critical gaps and omissions in the book. A lot of concepts are just given to the reader without an explanation. For example, the first time you see tapply() mentioned, all it says you can use this to solve the problem. Similarly, the graphing is just given to the user as specific code examples which the user will then have a hard time adapting to other scenarios because no fundamental understanding is gained.
The never ending references to the R help are annoying. It's ok to say it a few times, but it just looks like the same paragraph is included with each section.
Overall, as a tutorial, it fails. As a reference to R I found it somewhat useful, however answers of the kind provided in the book are frequently found on sites like stackoverflow as well.
I recommend "Elelementary Statistics - Picturing the world" for a sound approach to learning statistics. The 2011 fifth edition can be had for a reasonable price. Check out MarinStatsLectures on youtube for an introduction to R and statistics.
17 of 21 people found the following review helpful.
Interesting book, but formatting varies between kindle devices
By Julian Cook
This is an interesting book that is really three very separate parts: An intro to R, coverage of bayesian statistics and a look at clustering methods using a GPU.
As an intro it is ok (I mean the non-bayesian sections I and II), but frankly the amount of time devoted to covering data frames is ludicrously small for such an important topic. If people are to do real work in R, they definitely need to know how to manipulate their data, including importing, ordering, subsetting etc. Same comment applies to graphics. I think that almost everything I do that is exploratory, is with the intention of graphing it at the end of the process. This aspect is barely mentioned until bayesian statistics (part III).
The highlight for most is the GPU clustering material which is fascinating. The big drawback for many is that the corresponding library is linux only, which was disappointing.
I noticed that the formatting of the R output is good on the cloud reader but faulty on a Touchpad kindle reader - where the R output is not properly formatted with a fixed font - so is difficult to follow in places.
6 of 7 people found the following review helpful.
Overview
By Anand Gavai
This e-book gives a good overview on Bayesian statistics as well as classical statistics with a separate chapter on high performance computing with GPU. The first two parts on statistics (Bayesian as well as classical) are a nice reference material and gives analogies between the two approaches and shows the functions and tools that are available in R. Comparing with price and material ratio, this book stands out and is definitely worth the money. This book is more on the lines of lecture notes than an actual book.
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