rowVars: Variance estimates for each row (column) in a matrix

In matrixStats: Methods that apply to rows and columns of a matrix

Description

Variance estimates for each row (column) in a matrix.

Usage

 rowVars(x, na.rm=TRUE, center=NULL, ...)
 colVars(x, na.rm=TRUE, center=NULL, ...)

Arguments

x	A numeric NxK matrix.
center	(optional) The center, defaults to the row means.
na.rm	If TRUE, NAs are excluded first, otherwise not.
...	Additional arguments passed to rowMeans() and rowSums().

Value

Returns a numeric vector of length N (K).

Author(s)

Henrik Bengtsson

See Also

See rowMeans() and rowSums() in colSums().

Examples

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))

matrixStats documentation built on May 2, 2019, 4:52 p.m.