Dear all,
Given vectors "x" and "y", I would like to compute the proportion of
entries that are equal, that is, mean(x == y).
Now, suppose I have the following matrix:
n <- 1e2
m <- 1e4
X <- matrix(sample(0:2, m*n, replace = TRUE), ncol = m)
I am interested in calculating the above proportion for every pairwise
combination of rows. I came up with the following:
myd <- function(X, p = NROW(X)){
D <- matrix(NA, p, p)
for(i in 1:p) for(j in 1:p) if(i > j) D[i, j] <- mean(X[i, ] == X[j,])
D
}
system.time(d <- myd(X))
However, in my application n and m are much more larger than in this
example and the computational time might be an issue. I would very much
appreciate any suggestions on how to speed the "myd" function.
Note: I have done some experiments with the dist() function and despite
being much, much, much faster than "myd", none of the default distances
fits my needs. I would also appreciate any suggestions on how to include
"my own" distance function in dist().
Thank you very much for your time.
Best regards,
Jorge Velez.-
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