Silver_80 - 2 years ago 119

R Question

I have a function return list of list, I would like to find the standard deviation of the matrices of my output. The output of my function is a list of two list. I tried this code but it return me NAN. Since my function is complex, then I use this example from another question please see here since it is quite close to what I am trying to do.

`> A <- matrix(c(1:9), 3, 3)`

> A

[,1] [,2] [,3]

[1,] 1 4 7

[2,] 2 5 8

[3,] 3 6 9

> B <- matrix(c(2:10), 3, 3)

> B

[,1] [,2] [,3]

[1,] 2 5 8

[2,] 3 6 9

[3,] 4 7 10

> my.list1 <- list(A, B)

so the mean of the first list is:

`[,1] [,2] [,3]`

[1,] 1.5 4.5 7.5

[2,] 2.5 5.5 8.5

[3,] 3.5 6.5 9.5

Then the standard deviation will be:

`[,1] [,2] [,3]`

[1,] 0.7071068 0.7071068 0.7071068

[2,] 0.7071068 0.7071068 0.7071068

[3,] 0.7071068 0.7071068 0.7071068

> c <- matrix(c(1:9), 3, 3)

> c

[,1] [,2] [,3]

[1,] 1 4 7

[2,] 2 5 8

[3,] 3 6 9

> d <- matrix(c(2:10), 3, 3)

> d

[,1] [,2] [,3]

[1,] 2 5 8

[2,] 3 6 9

[3,] 4 7 10

> my.list2 <- list(c, d)

my.list <-list(my.list1,my.list2)

How can I get the standard deviation of my matrices on an element by element for the list?

Recommended for you: Get network issues from **WhatsUp Gold**. **Not end users.**

Answer Source

You could bind your lists into an array, or perhaps make your function return an array(?), then you could use `apply()`

to apply your chosen functions...

```
A <- matrix(1:9, 3, 3)
B <- matrix(2:10, 3, 3)
my.list1 <- list(A, B)
c <- matrix(1:9, 3, 3)
d <- matrix(2:10, 3, 3)
my.list2 <- list(c, d)
```

Create array from all 4 lists

```
my.array1 <- abind::abind(c(my.list1, my.list2), along = 3)
```

Find the `mean()`

of the required dimension

```
apply(my.array1, c(1, 2), mean)
apply(my.array1, c(1,2), sd)
```

**Output**

```
[,1] [,2] [,3]
[1,] 1.5 4.5 7.5
[2,] 2.5 5.5 8.5
[3,] 3.5 6.5 9.5
```

Recommended from our users: **Dynamic Network Monitoring from WhatsUp Gold from IPSwitch**. ** Free Download**