Comparing for, apply and vectorised functions

speed.R

m <- matrix(runif(1e6),nrow=10000)

## append to result vector -- slow
res1 <- NULL
t1 <- system.time(for (i in 1:1000) res1[i] <- sum(m[i,]))

## initialise to full length -- fast
res2 <- numeric(1000)
t2 <- system.time(for (i in 1:1000) res2[i] <- sum(m[i,]))

## using apply -- slowest!
t3 <- system.time(res3 <- apply(m,1,sum))

## vectorised function -- fastest
t4 <- system.time(res4 <- rowSums(m))

cbind(t1,t2,t3,t4)
##              t1    t2    t3    t4
## user.self  0.01 0.010 0.120 0.000
## sys.self   0.00 0.000 0.000 0.000
## elapsed    0.01 0.007 0.115 0.003
## user.child 0.00 0.000 0.000 0.000
## sys.child  0.00 0.000 0.000 0.000