Posts Tagged ‘ statistical computing ’

ThinkStats … in R (including Example 1.2)

March 4, 2012

ThinkStats (by Allen B. Downey) is a good book to get you familiar with statistics (and even Python, if you’ve done some scripting in other languages). I thought it would be interesting to present some of the examples & exercises in the book in R. Why? Well, once you’ve gone through the material in a

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Parallel JAGS RNGs

July 23, 2011

As a matter of convention, we usually run 3 or 4 chains in JAGS. By default, this gives rise to chains that draw samples from 3 or 4 distinct pseudorandom number generators. I didn’t go and check whether it does things 111,222,333 or 123,123,123, but in any event the “parallel chains” in JAGS are samples

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R on the cloud

July 9, 2011

Just as scientists should never really have to think much about statistics, I feel that, in an ideal world, statisticians would never have to worry about computing. In the real world, though, we have to spend a lot of time building our own tools.It would be great if we could routinely run R with speed and memory limitations...

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Computational Statistics

May 9, 2010
Computational Statistics

Do not resort to Monte Carlo methods unnecessarily. When I received this 2009 Springer-Verlag book, Computational Statistics, by James Gentle a while ago, I briefly took a look at the table of contents and decided to have a better look later… Now that I have gone through the whole book, I can write a short

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Mango solutions

RStudio homepage

Zero Inflated Models and Generalized Linear Mixed Models with R

Quantide: statistical consulting and training


CRC R books series

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