RudiSophieson - 1 month ago 5

R Question

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

`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.

Answer

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
```

Source (Stackoverflow)

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