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dear all, I would like to center and scale some columns of a data frame (these include NAs) according to the levels of an index (list of factors from the same data frame). I tried to code it using for loops but gave up. I guess there is a straightforward way to achieve this: any hint welcome! thanks a lot thomas -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-

How can I add a color bar to show the color scales to what is generated by image(), similar to the one in figures generated by filled.contour()? Thanks. Y. C. Tao

Full_Name: thomas cornulier Version: 1.9.0 and 1.9.1 OS: Win XP Submission from: (NULL) (194.254.155.62) the following function produces R crashes under windows XP platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status major 1 minor...

Hi! Some weeks ago I discovered R. Now, I have a somewhat complicated task and am not sure whether R is the right tool to solve it. I got data of several series or measurements where I have to find the two inflection points. I did a linear regression (with ^2 and ^3 arguments), the problem there was that I had to look only at a very narrow band of measurement in order to get the

I have to solve a clustering problem. My first step is to determinate the number of clusters, that's why I 'm using the Calinski index ( [tr(b)/(k-1)]/[tr(w)/(k-1)] ) which i try to maximize to have the best number of clusters. A function is already implemented in R to calculate this index : clustIndex(cl,x, index="calinski") where cl is the result of a clustering method ,

Recently, I have been working with some data that look like two overlapping gaussian distributions. I would like to either 1) determine the mean and SD for each of the two distributions OR 2) get some (bayesian ?) statistic that estimates how likely an observation is to belong to the left-hand or right-hand distribution In case I'm using the wrong language, my data looks something like