Reputation: 271
I have a list in which each element is a matrix.
set.seed(123)
m1 <- matrix(sample(c(1:10), size = 9, replace = TRUE), ncol = 3, nrow = 3)
m2 <- matrix(sample(c(1:10), size = 9, replace = TRUE), ncol = 3, nrow = 3)
m3 <- matrix(sample(c(1:10), size = 9, replace = TRUE), ncol = 3, nrow = 3)
m <- list(m1, m2, m3)
m
[[1]]
[,1] [,2] [,3]
[1,] 3 9 6
[2,] 8 10 9
[3,] 5 1 6
[[2]]
[,1] [,2] [,3]
[1,] 5 7 9
[2,] 10 6 3
[3,] 5 2 1
[[3]]
[,1] [,2] [,3]
[1,] 4 7 7
[2,] 10 7 8
[3,] 9 10 6
I want to calculate the standard deviation of each pair considering all three matrices. So for cell [1,1] the standard deviation would be:
sd(c(3, 5, 4))
My final matrix should look like this:
[,1] [,2] [,3]
[1,] 1.00 1.15 1.53
[2,] 1.15 2.08 3.21
[3,] 2.31 4.93 2.89
How can I achieve this in R without a loop over all three matrices?
Many thanks in advance.
Upvotes: 5
Views: 2610
Reputation: 389135
Another option is
matrix(apply(sapply(1:9, function(x) unlist(m)[seq(x, length(unlist(m)), 9)]), 2, sd),
ncol = 3)
# [,1] [,2] [,3]
#[1,] 1.000000 1.154701 1.527525
#[2,] 1.154701 2.081666 3.214550
#[3,] 2.309401 4.932883 2.886751
Upvotes: 1
Reputation: 887511
It is better to convert this to array
by unlist
ing the list
to a vector
, convert it to a 3D array
and get the sd
with apply
round(apply(array(unlist(m), c(3, 3, 3)), c(1,2), sd),2)
# [,1] [,2] [,3]
#[1,] 1.00 1.15 1.53
#[2,] 1.15 2.08 3.21
#[3,] 2.31 4.93 2.89
Upvotes: 5