distpar {amap} | R Documentation |
This function computes and returns the distance matrix computed by using the specified distance measure to compute the distances between the rows of a data matrix.
distpar(x, method = "euclidean", nbproc = 2, diag = FALSE, upper = FALSE)
x |
numeric matrix or (data frame) or an object of class
"exprSet". Distances between the rows of
x will be computed. |
method |
the distance measure to be used. This must be one of
"euclidean" , "maximum" , "manhattan" ,
"canberra" , "binary" , "pearson" ,
"correlation" or "spearman" .
Any unambiguous substring can be given. |
nbproc |
integer, Number of subprocess for parallelization |
diag |
logical value indicating whether the diagonal of the
distance matrix should be printed by print.dist . |
upper |
logical value indicating whether the upper triangle of the
distance matrix should be printed by print.dist . |
An object of class "dist"
.
Antoine Lucas and Sylvain Jasson, Using amap and ctc Packages for Huge Clustering, R News, 2006, vol 6, issue 5 pages 58-60.
x <- matrix(rnorm(100), nrow=5) ## compute dist with 8 threads distpar(x,nbproc=8) ## compute pearson dist with 8 threads distpar(x,nbproc=8,method="pearson")