Hello I'm trying to solve this problem without using a for loop but I have so far failed to find a solution.
I have two matrices of K columns each, e.g. (K=5), and with numbers of row N_A and N_B respectively A = (1 5 3 8 15; 2 7 20 11 13; 12 19 20 21 43) B = (2 6 30 8 16; 3 8 19 11 13) (the actual matrices have hundreds of thousands of entry, that's why I'm keen to avoid "for" loops) And what I need to do is to apply a function which counts the number of common elements between ANY row of A and ANY row of B, giving a result like this: A1 vs B1: 1 # (8 is a common element) A1 vs B2: 1 # (8 is a common element) A2 vs B1: 1 # (2 is a common element) A2 vs B2: 1 # 11, 13 are common elements Etc. I've built a function that counts the number of common elements between two vectors, based on the intersect function in the R manual common_elements <- function(x,y) length(y[match(x,y,nomatch=0)]) And a double loop who solves my problem would be something like (pseudo-code) For(i in 1:N_A){ for(j in 1:N_B){ ce(i,j)=common_elements(a(i),b(j)) } } Is there an efficient, clean way to do the same job and give as an output a matrix N_A x N_B such as that above? Thanks a lot for your help Regards Pietro ______________________________________________________________________ For information pertaining to Willis' email confidentiality and monitoring policy, usage restrictions, or for specific company registration and regulatory status information, please visit http://www.willis.com/email_trailer.aspx We are now able to offer our clients an encrypted email capability for secure communication purposes. If you wish to take advantage of this service or learn more about it, please let me know or contact your Client Advocate for full details. ~W67897 ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.