Thanks to Prof. Ripley, Jens, Roger, and Sean. knn1 is exactly what I'm looking for.

Thanks again,
Sundar


Prof Brian Ripley wrote:
Sounds like knn classification. See function knn1 in package class.


knn(A, B, 1:nrow(A))


gives the same answers as your loop code, and is just a carefully tuned C equivalent.

There are faster ways to do this by preprocessing set A discussed e.g. in my PRNN book but your numbers took only 11s on my PC.

On Tue, 27 Jan 2004, Sundar Dorai-Raj wrote:


Hi all,
Say I have a matrix A with dimension m x 2 and matrix B with dimension n x 2. I would like to find the row in A that is closest to the each row in B. Here's an example (using a loop):


set.seed(1)
A <- matrix(runif(12), 6, 2) # 6 x 2
B <- matrix(runif(6), 3, 2)  # 3 x 2
m <- vector("numeric", nrow(B))
for(j in 1:nrow(B)) {
  d <- (A[, 1] - B[j, 1])^2 + (A[, 2] - B[j, 2])^2
  m[j] <- which.min(d)
}

All I need is m[]. I would like to accomplish this without using the loop if possible, since for my real data n > 140K and m > 1K. I hope this makes sense.

Thanks,
Sundar

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