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There are, at least :), two ways to compute the principal component analysis of a data set in R. The first one is from scratch computing eigenvectors and eigenvalues. It works as follows # # From scratch # cbind(1:10,1:10 + 0.25*rnorm(10)) -> myData myData - apply(myData,2,mean) -> myDataZM cov(myDataZM) -> cvm eigen(cvm,TRUE) -> eCvm t(eCvm$vector%*%t(myDataZM)) -> newMyData This simple code just transforms the data to align it with the principal components obtained....

I have been running into some problems with a feed generator I am using (yes, it is the one in WordPress MU, long story). However I found a useful tool, an on-line feed validator for Atom and RSS.

Need one? Check Eclipse.

I have run into a couple of plugins for Eclipse to compute several measure about the code you have in your project. The one I currently use is Eclipse Metrics Plugin. This Eclipse plugin calculates various metrics for your code during build cycles and warns you, via the Problems view, of range violations for each metric. This allows you to stay continuously aware of the health of your code base. You may also export the metrics to HTML for public display or to CSV format for further analysis....

Continuation of GE498-ECI, Lecture 12: Social means interaction (I): Learning what you like.