Variance estimates for each row (column) in a matrix
Variance estimates for each row (column) in a matrix.
rowVars(x, rows = NULL, cols = NULL, na.rm = FALSE, center = NULL, dim. = dim(x), ...) colVars(x, rows = NULL, cols = NULL, na.rm = FALSE, center = NULL, dim. = dim(x), ...)
x |
|
rows, cols |
A |
na.rm |
If |
center |
(optional; a vector or length N (K)) If the row (column) means are already estimated, they can be pre-specified using this argument. This avoid re-estimating them again. (*Warning: If biased estimated are given, the estimate of the spread will also be biased.*) If NULL (default), the row/column means are estimated internally. |
dim. |
An |
... |
Additional arguments passed to |
Henrik Bengtsson
See rowMeans() and rowSums() in
colSums().
set.seed(1) x <- matrix(rnorm(20), nrow = 5, ncol = 4) print(x) # Row averages print(rowMeans(x)) print(rowMedians(x)) # Column averages print(colMeans(x)) print(colMedians(x)) # Row variabilities print(rowVars(x)) print(rowSds(x)) print(rowMads(x)) print(rowIQRs(x)) # Column variabilities print(rowVars(x)) print(colSds(x)) print(colMads(x)) print(colIQRs(x)) # Row ranges print(rowRanges(x)) print(cbind(rowMins(x), rowMaxs(x))) print(cbind(rowOrderStats(x, which = 1), rowOrderStats(x, which = ncol(x)))) # Column ranges print(colRanges(x)) print(cbind(colMins(x), colMaxs(x))) print(cbind(colOrderStats(x, which = 1), colOrderStats(x, which = nrow(x)))) x <- matrix(rnorm(2400), nrow = 50, ncol = 40) # Row standard deviations d <- rowDiffs(x) s1 <- rowSds(d) / sqrt(2) s2 <- rowSds(x) print(summary(s1 - s2)) # Column standard deviations d <- colDiffs(x) s1 <- colSds(d) / sqrt(2) s2 <- colSds(x) print(summary(s1 - s2))
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.