I have been studying in the major of statistics for more than 5 years (and there are still at least 3 years left), and I find one significant difference between the disciplines of pure mathematics and statistics: usually statistics can be imagined in a very practical way, while it is not true for mathematics. For example, I believe everyone can imagine why k-Nearest Neighbor technique works, but not everyone can *imagine* why Taylor expansion technique works *although we can prove it*!

Thus I wrote such a package: just for better understanding of statistical techniques and data analysis.

This package "animation" is available in CRAN now; the source code as well as Windows binary can be downloaded at:

http://cran.r-project.org/web/packages/animation/l

You may install by R CMD INSTALL after downloading the source or simply use *install.packages()* in R:

install.packages("animation")

I have written a vignette for this package explaining some details for animations in statistics, and this vignette is also an animation gallery (see Chapter 5).

Running animations either inside R (in graphical devices) or outside R (in HTML pages) are OK, as I provided an argument saveANI (actually in the argument control using the function *ani.control()*) to decide whether to save PNG files.

By *ani.start()*, specifying saveANI = TRUE, and *ani.stop()*, you can generate an HTML page containing the animation; or if saveANI = FALSE, the animations will be shown inside R graphical devices.

For further information, please check the help pages or the vignette.

For example, to create HTML animation pages, just use *ani.start()* and *ani.stop()*, otherwise if you just want to watch animations inside R, please check those animation functions such as *brownian.motion()*, *cv.ani()*, *kmeans.ani()*, *knn.ani()*, etc.

Please make sure R has write permission to your disk when saving animations (saveANI = TRUE).

I'll explain every animation function in the vignette (Chapter 5) as well as in this site.