lapply and for

Agustin Lobo <alobo at ija.csic.es> writes:

Given a list as such:

milista

$"1":
[1] 23 25 11

$"2":
[1] 34  2

$"3":
[1]   12    1    0 1050    2

What's faster:

a <- NULL
for (i in names(milista)){

+ a <- c(a,(mean(milista[[i]])))
+ }

or

a <- lapply(milista,mean)


?

(I understand that the second option
is nicer and more compact, but is it
faster?).

Probably, since the first option is far from optimal itself:

a <- numeric(length(milista))
n <- 0
for (i in milista) 
   a[n <- n + 1] <- mean(i)

or 

n <- length(milista)
a <- numeric(n)
for (i in 1:n)
    a[i] <- mean(milista[[i]])

should both be faster. lapply essentially *is* the latter, but has the
for loop coded in C, so should be faster, but not by a huge amount.
For very short lists, the "red tape" at the beginning and end of
lapply() might pull in the opposite direction.

Why not just try it and see?

O__  ---- Peter Dalgaard             Blegdamsvej 3  
  c/ /'_ --- Dept. of Biostatistics     2200 Cph. N   
 (*) \(*) -- University of Copenhagen   Denmark      Ph: (+45) 35327918
~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk)             FAX: (+45) 35327907
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