Displaying 2 results from an estimated 2 matches for "mahadist".
2008 Oct 09
2
vectorization instead of using loop
...s. We want to
calculate Mahalanobis distances, which take into account the covariance
among variables.
Below is the piece of code we wrote ("covmat" in the function below is the
variance-covariance matrix among variables in Data that has to be fed into
mahalonobis function we are using).
mahadist = function(x, covmat) {
dismat = matrix(0,ncol=nrow(x),nrow=nrow(x))
for (i in 1:nrow(x)) {
dismat[i,] = mahalanobis(as.matrix(x), as.matrix(x[i,]), covmat)^.5
}
return(dismat)
}
This piece of code works, but it is very slow. We were wondering if it's at
all possible to somehow vect...
2008 Oct 07
1
vectorization of a loop for mahalanobis distance calculation
.... We want to calculate
Mahalanobis distances, which take into account the covariance among
variables.
Below is the piece of code we wrote ("covmat" in the function below is the
variance-covariance matrix among variables in Data that has to be fed into
mahalonobis function we are using).
mahadist = function(x, covmat) {
dismat = matrix(0,ncol=nrow(x),nrow=nrow(x))
for (i in 1:nrow(x)) {
dismat[i,] = mahalanobis(as.matrix(x), as.matrix(x[i,]), covmat)^.5
}
return(dismat)
}
This piece of code works, but it is very slow. We were wondering if it's at
all possible to someho...