mtlb_var

Matlab var emulation function

Arguments

:x a real or a complex vector or matrix. : :s a real scalar or real vector.

• If x is a vector, s is the variance of x.
• If x is a matrix, s is a row vector containing the variance of each column of x.

: :w type of normalization to use. Valid values are, depending on the number of columns m of x :

• w = 0 : normalizes with m-1, provides the best unbiased estimator of the variance (this is the default).
• w = 1: normalizes with m, this provides the second moment around the mean.

: :dim the dimension along which the variance is computed (default is

1, i.e. column by column). If dim is 2, the variance is computed row by row.

:

Description

This function computes the variance of the values of a vector or matrix x. It provides the same service as Octave and Matlab. It differs from Scilab’s variance primitive:

• mtlb_var returns a real (i.e. with a zero imaginary part) variance, even if x is a complex vector or matrix. The Scilab variance primitive returns a complex value if the input vector x is complex and if no option additionnal is used.
• Whatever the type of the input data x (i.e. vector or matrix), mtlb_var computes the variance either on dimension 1 or on dimension 2 while, if no option is passed to the Scilab’s variance primitive, the variance is computed on all dimension at once.

Examples

The following 3 examples illustrates the use of the mtlb_var function. In the first case, a column vector is passed to the function, which returns the value 750. In the second case, a matrix is passed to the function, which returns the row vector [0.16 0.09]. In the third case, a complex column vector is passed to the function, which returns a value close to 2.

x = [10; 20; 30; 40; 50; 60; 70; 80; 90];
computed = mtlb_var(x);

x = [0.9    0.7
    0.1    0.1
    0.5    0.4];
computed = mtlb_var(x);

N=1000;
x = `grand`_(N,1,'nor',0,1) + %i*`grand`_(N,1,'nor',0,1);
computed = mtlb_var(x);

See Also

• variance variance of the values of a vector or matrix