Weighted mean by row

Question

I have the following data:

a=c(1:10)
b=c(16:25)
c=c(24:33)
wa=c(3,7,3,3,3,3,3,3,3,1)
wb=c(3,2,3,3,3,3,3,3,3,8)
wc=c(4,1,4,4,4,4,4,4,4,1)
z=data.frame(a,b,c,w         


        

Answer 1

This seems to do the trick:

> apply(z, 1, function(x) weighted.mean(x[1:3], x[4:6]))
 [1] 14.7  7.3 16.7 17.7 18.7 19.7 20.7 21.7 22.7 24.3

This will probably be a bit faster, though less clear as to what's going on:

> rowSums(z[,1:3] * z[,4:6]) / rowSums(z[,4:6])
 [1] 14.7  7.3 16.7 17.7 18.7 19.7 20.7 21.7 22.7 24.3