var - Variance
Syntax
V = var(X)
V = var(X,1)
V = var(X,w)
V = var(X,w,dim)
Description
V = var(X) returns the variance
of X for vectors. For matrices, var(X)is
a row vector containing the variance of each column of X.
For N-dimensional arrays, var operates along the first nonsingleton dimension
of X. The result V is an unbiased estimator of the variance
of the population from which X is drawn, as long as X consists
of independent, identically distributed samples.
var normalizes V by N-1 if N>1,
where N is the sample size. This is an unbiased estimator
of the variance of the population from which X is drawn,
as long as X consists of independent, identically distributed
samples. For N=1, V is normalized by N.
V = var(X,1) normalizes by N and
produces the second moment of the sample about its mean.var(X,0)
is equivalent to var(X).
V = var(X,w) computes the variance
using the weight vector w. The length of w must
equal the length of the dimension over which var operates,
and its elements must be nonnegative. The elements of w must
be positive. var normalizes w to sum
of 1.
V = var(X,w,dim) takes the variance
along the dimension dim of X. Pass in 0 for w to
use the default normalization by N-1, or 1 to use N.
The variance is the square of the standard deviation (STD).
See Also
corrcoef, cov, mean, median, std
 | vander | | var (timeseries) |  |
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