Hi, I am working on a dataset in which a number of venture capitalists invest in a number of firms. What I am creating is an asymmetric matrix M in which m(ij) is the volume (sum) of coinvestments of VC i with VC j (i.e., how much has VC i invested in companies that VC j also has investments in). The output should look like the "coinvestments" matrix produced with the code below. If possible I would like to avoid loops and optimize the code for speed because the real data is huge. If anybody has suggestions, I would be grateful. invest=c(20,50,40,30,10,20,20,30,40) vc=rep(c('A','B','C'),each=3) company=c('E','F','G','F','G','H','G','H','I') data=data.frame(vc,company,invest) data #data inv.mat=tapply(invest,list(vc,company),sum) inv.mat=replace(inv.mat,which(is.na(inv.mat)==T),0) inv.mat #investment matrix exist.mat=inv.mat>0 coinvestments<-matrix(0,nrow=length(unique(vc)),ncol=length(unique(vc))) for(i in unique(vc)){ for(j in unique(vc)){ i.is=which(unique(vc)==i) j.is=which(unique(vc)==j) i.invests=exist.mat[i,] j.invests=exist.mat[j,] which.i=which(i.invests==T) which.j=which(j.invests==T) i.invests.with.j=which.i[which.i%in%which.j] coinvestments[i.is,j.is]=sum(inv.mat[i.is,i.invests.with.j]) } } coinvestments system.time( for(i in unique(vc)){ for(j in unique(vc)){ i.is=which(unique(vc)==i) j.is=which(unique(vc)==j) i.invests=exist.mat[i,] j.invests=exist.mat[j,] which.i=which(i.invests==T) which.j=which(j.invests==T) i.invests.with.j=which.i[which.i%in%which.j] coinvestments[i.is,j.is]=sum(inv.mat[i.is,i.invests.with.j]) } } ) Thanks much, Daniel -- View this message in context: http://r.789695.n4.nabble.com/Avoiding-loops-in-creating-a-coinvestment-matrix-tp3424298p3424298.html Sent from the R help mailing list archive at Nabble.com.