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Dear R´ers, How can I create one single factor variable from two variables incorporating all possible combinations of the values?? test<-sample(c("A",NA,"B"),100,replace=T) test2<-sample(c("E",F,"A"),100,replace=T) tes<-cbind(test,test2) pseduocode: r<-function(test,test2) r AE AF AA NAE NAF NAA BE BF BA //M [[alternative HTML

I'm using R to manipulate some data for testing nebulisers. I have a data frame as follows: Volt ABal 0.4208 A1 0.3982 AF 0.4353 B1 0.3954 BF 0.4355 C1 0.3975 CF 0.4345 I also have a calibration curve loaded Voltage NaF LogNaF 1 0.3588 20 1.30103 2 0.3990 100 2.00000 3 0.4391 500 2.69897 If I try to

Hi, I just tried to install a CentOS 5 desktop on very recent hardware, an Acer desktop machine. The installer stopped short very early. I gave Ubuntu 8.04 a shot, and it installed without a problem. Now what can I do about this? Is there a way to use some "enhanced" kernel (like the centos.plus kernel) to perform the install? I guess what's missing there is a specific driver

Hello, My question is : is there a way to have Icecast buffer the input / increase the input buffering ? Even though the latency would increase ? Why : On some radio streams, the listeners to a Icecast stream experience very frequent silences / disconnections. I strongly suspect that the source has a slow/bursty connection to Icecast so that the data sent to the Icecast server arrives in

This smells like a bug to me. The error is triggered by the line: variables <- eval(predvars, data, env) inside model.frame.default(). At that point, na.action has not been applied, so poly() ended being called on data that still contains missing values. The qr() that issued the error is for generating the orthogonal basis when evaluating poly(), not for fitting the linear model itself.

This smells like a bug to me. The error is triggered by the line: variables <- eval(predvars, data, env) inside model.frame.default(). At that point, na.action has not been applied, so poly() ended being called on data that still contains missing values. The qr() that issued the error is for generating the orthogonal basis when evaluating poly(), not for fitting the linear model itself.