Row Sums/Means of Sparse Symmetric Matrices
Compute the row (column) sums or means for a sparse symmetric (distance) matrix.
rowSums.dist(x, na.rm = FALSE) rowMeans.dist(x, na.rm = FALSE, diag = TRUE) colSums.dist(x, na.rm = FALSE) colMeans.dist(x, na.rm = FALSE, diag = TRUE)
x |
an object of class |
na.rm |
logical, should missing values (including |
diag |
logical, should the diagonal elements be included in the computation? |
These functions are more efficient than expanding an object of
class dist to matrix and using rowSums or rowMeans.
colSums and colMeans are provided for convenience.
However, note that due to symmetry the result is always the
same as for rowSums or rowMeans.
A numeric vector of row sums.
Christian Buchta
as.matrix, as.dist, and rowSums.
## x <- matrix(runif(10*2),ncol=2) d <- dist(x) rowSums(as.matrix(d)) rowSums.dist(d) # the same rowMeans(as.matrix(d)) rowMeans.dist(d) # the same rowMeans.dist(d, diag = FALSE) # not the same ## NAs d[3] <- NA rowSums.dist(d, na.rm = TRUE) rowMeans.dist(d, na.rm = TRUE)
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