"Francisco J. Bido" <[EMAIL PROTECTED]> writes: > Hi There, > > While looking through the mailing list archive, I did not come across > a simple minded example regarding the creation of dummy variables. > The Gauss language provides the command "y = dummydn(x,v,p)" for > creating dummy variables. > > Here: > > x = Nx1 vector of data to be broken up into dummy variables. > v = Kx1 vector specifying the K-1 breakpoints > p = positive integer in the range [1,K], specifying which column > should be dropped in the matrix of dummy variables. > > y = Nx(K-1) matrix containing the K-1 dummy variables. > > My recent mailing list archive inquiry has led me to examine R's > "model.matrix" but it has so many options that I'm not seeing the > forest because of the trees. Is that really the easiest way? or is > there something similar to the dummydn command described above? > > > To provide a concrete scenario, please consider the following. Using > the above notation, say, I had: > > > x <- c(1:10) #data to be broken up into dummy variables > v <- c(3,5,7) #breakpoints > p = 1 #drop this column to avoid dummy variable trap > > How can I get a matrix "y" that has the associated dummy variables for > columns?
Don't. Consider why you want the dummy variables. You probably want to use them in the specification of a statistical model and R's model specification language automatically expands a factor variable into a set of contrasts. Try data(PlantGrowth) fm = lm(weight ~ group, data = PlantGrowth) summary(fm) and you will see that the `group' factor has been expanded to two of the three indicator variables (if you use the default setting for contrasts - other possibilities exist). You can check explicitly how the model matrix is created with model.matrix(fm) The model specification facilities in R are much more flexible than most other languages and you almost never need to create indicators explicitly. ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
