[英]Calculate mean of colnames and rownames set in matrix in R
Apologies if this has been asked elsewhere but I couldn't find an answer. 抱歉,是否有人在其他地方提出过此要求,但我找不到答案。
I'm attempting to calculate the mean of a matrix I've created, using colMeans and rowMeans. 我正在尝试使用colMeans和rowMeans计算我创建的矩阵的平均值。 The mean values are what I want to populate the matrix with, and have set the rows and columns using vectors
平均值是我要用来填充矩阵的值,并且已经使用矢量设置了行和列
Currently my code looks like this: 目前,我的代码如下所示:
A = matrix(ncol = (14), # number of columns in matrix
nrow = (10), # number of rows in matrix
colMeans(A, na.rm = FALSE, dims = colnames(A)),
rowMeans(A, na.rm = FALSE, dims = rownames(A)),
byrow = TRUE)
colnames(A) c("2","4","6","8","10","12","14","16","18","20","22","24","26","28")
rownames(A) <- c("10","20","30","40","50","60","70","80","90","100")
A
Running this returns a matrix with NA values. 运行此命令将返回具有NA值的矩阵。
Expected output would be a matrix like below, where NA values are replaced by the mean of the column and row numbers. 预期的输出将是一个如下所示的矩阵,其中NA值由列数和行数的平均值代替。
For example the first intersection would equal 6, as 2+10/2 例如,第一个交集等于6,即2 + 10/2
2 4 6 8 10 12 14 16 18 20 22 24 26 28
10 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
20 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
30 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
40 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
50 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
60 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
70 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
80 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
90 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA
This is essentially what you want using the outer
function. 本质上,这就是您要使用
outer
函数所需要的。 Note that t
transposes the matrix so it's the right way round that you specify above.It could also just be outer(B,A, fn)
请注意,
t
转置矩阵,因此这是您在上面指定的正确方法,它也可以是external outer(B,A, fn)
A<-seq(2,28,2)
B<-seq(10,100,10)
fn<-function(A,B)(A+B)/2
t(outer(A,B, fn))
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 6 7 8 9 10 11 12 13 14 15 16 17 18 19
[2,] 11 12 13 14 15 16 17 18 19 20 21 22 23 24
[3,] 16 17 18 19 20 21 22 23 24 25 26 27 28 29
[4,] 21 22 23 24 25 26 27 28 29 30 31 32 33 34
[5,] 26 27 28 29 30 31 32 33 34 35 36 37 38 39
[6,] 31 32 33 34 35 36 37 38 39 40 41 42 43 44
[7,] 36 37 38 39 40 41 42 43 44 45 46 47 48 49
[8,] 41 42 43 44 45 46 47 48 49 50 51 52 53 54
[9,] 46 47 48 49 50 51 52 53 54 55 56 57 58 59
[10,] 51 52 53 54 55 56 57 58 59 60 61 62 63 64
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