var

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Compute the variance, covariance or covariance-matrix.


Usage 1
var(xvector)
Result 1
The variance v of vector x.
v = sum( (x-avr(x))?^2 ) / (nrow(x)-1)
v = (x-avr(x))^2 / (nrow(x)-1)

Usage 2
var(xvector, yvector)
Result 2
The covariance v of the vectors x and y.
v = sum( (x-avr(x) ?* (y-avr(y)) ) / (nrow(x)-1)
v = ((x-avr(x) * (y-avr(y))) / (nrow(x)-1)

Usage 3
var(xmatrix)
var(xmatrix, yscalar)
var(xmatrix, yvector)
Result 3
The covariance matrix v of the column vectors of x.
v[i,j] = sum( (x[*,i]-a[i]) ?* (x[*,j]-a[j]) ) / (nrow(x)-1) , with: i,j = 0..ncol(x)-1
The column averages a[i] are computed as follows:
y not supplied a[i] = avr(x[*,i])
yscalar a[i] = y
yvector a[i] = y[i]
See also
avr, dev, corr, dist, svd

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