> Didn't you simply try: > > > A<-matrix(c(1.1,1.2,1.3,1.4,1.5,1.6),ncol=3) > > B<-matrix(c(2.1,2.2,2.3,2.4,2.5,2.6),ncol=3) > > C<-matrix(c(3.1,3.2,3.3,3.4,3.5,3.6),ncol=3) > > A > [,1] [,2] [,3] > [1,] 1.1 1.3 1.5 > [2,] 1.2 1.4 1.6 > > B > [,1] [,2] [,3] > [1,] 2.1 2.3 2.5 > [2,] 2.2 2.4 2.6 > > C > [,1] [,2] [,3] > [1,] 3.1 3.3 3.5 > [2,] 3.2 3.4 3.6 > > rbind(A,B,C) > [,1] [,2] [,3] > [1,] 1.1 1.3 1.5 > [2,] 1.2 1.4 1.6 > [3,] 2.1 2.3 2.5 > [4,] 2.2 2.4 2.6 > [5,] 3.1 3.3 3.5 > [6,] 3.2 3.4 3.6 > > rbind(A,A,A) > [,1] [,2] [,3] > [1,] 1.1 1.3 1.5 > [2,] 1.2 1.4 1.6 > [3,] 1.1 1.3 1.5 > [4,] 1.2 1.4 1.6 > [5,] 1.1 1.3 1.5 > [6,] 1.2 1.4 1.6 >
This would be adequate for low dimensional dataset e.g. the example you have give. What if you have a list of thousands of matrices. Is there an efficient way of doing this other than looping? ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html