# [R] Avoiding loops in creating a coinvestment matrix

From: Daniel Malter <daniel_at_umd.edu>
Date: Sun, 03 Apr 2011 17:16:04 -0500 (CDT)

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

```--
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