Reputation: 1029
I have two matrices
A = matrix(c(2, 2, 2, 3, 3, 3),nrow=3,ncol=2)
> A
[,1] [,2]
[1,] 2 3
[2,] 2 3
[3,] 2 3
B = matrix(c(2, 4, 3, 1, 5, 7),nrow=3, ncol=2)
> B
[,1] [,2]
[1,] 2 1
[2,] 4 5
[3,] 3 7
take the mean of all values in B that correspond to 3 in B: Create a matrix with only the means: Wanted matrix:
C
[,1] [,2]
[1,] 3 4.3
[2,] 3 4.3
[3,] 3 4.3
Upvotes: 0
Views: 71
Reputation: 1309
What about:
A <- matrix(c(2, 2, 2, 3, 3, 2, 3, 2), nrow=4, ncol=2)
B <- matrix(c(2, 4, 3, 1, 5, 7, 4, 2), nrow=4, ncol=2)
matrix(tapply(B, A, mean)[as.character(A)], nrow=nrow(A))
?
Upvotes: 1
Reputation: 23919
When the groups are not column specific this might help:
A <- matrix( c(2, 2, 2, 3, 3, 3),nrow=3,ncol=2)
B <- matrix(c(2, 4, 3, 1, 5, 7),nrow=3, ncol=2)
C <- matrix(nrow = dim(A)[1], ncol=dim(A)[2])
groups <- unique(c(A))
for(group in groups) {
C[which(A==group)] <- mean(B[which(A==group)])
}
If A contains NA
values, then use
groups <- na.omit(unique(c(A)))
Upvotes: 1