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I have a time series for two variables measured simultaneously, but at different intervals. The variables are not independent, so the patterns in the times series are very similar (one variable goes up when the other goes up, etc). For example, let's pretend my data look something like this (but with more noise)... var1_times<-c(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10) var1_values<-c(0,

Let's say I have a program that returns variables whose names may be any string within the vector NAMES=c("varA","varB","varC","varD","varE","varF"..."varZ"), but I do not ever know which ones have actually been created. So in one example output, "varA", "varC", and "varD" could exist, but

Doe anyone know of a way to print nice-looking, printer-friendly tables directly in the R plot window? This would be very handy for examining preliminary results from frequently used routines. I've hunted for this with no luck. All anyone seems to do is export text files to excel for formatting, or use the print(bla) function which just calls the numbers at the command line. There must be

So I've come across a few cases where complex outputs from functions will not write to tables. The most recent case involves the TukeyHSD function in the stats package. If I save the TukeyHSD call and print it, that obviously goes fine, but when I try writing to a table, I get an error message that says "cannot coerce class \multicomp\" into dataframe. What does this mean, and

I'm trying to figure out how to trigger a process from within R. I have an exectuable file that runs a Fortran model, but ideally, would like to run it from R. Note that I'm not talking about importing the function at all, passing variables, or anything complicated like that. I basically just want a script that "double-clicks" on a particular file and opens/runs it for me. The