rowVars {matrixStats} | R Documentation |
Variance estimates for each row (column) in a matrix.
rowVars(x, center=NULL, ...) colVars(x, ...)
x |
A numeric NxK matrix . |
center |
(optional) The center, defaults to the row means. |
... |
Additional arguments passed to rowMeans() and
rowSums() . |
Returns a numeric
vector
of length N (K).
Henrik Bengtsson (http://www.braju.com/R/)
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, 1), rowOrderStats(x, ncol(x)))) # Column ranges print(colRanges(x)) print(cbind(colMins(x), colMaxs(x))) print(cbind(colOrderStats(x, 1), colOrderStats(x, 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))