Programmer Guide/Command Reference/EVAL/var: Difference between revisions

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;Usage 1: '''<code>var(''x''<sub>vector</sub>)</code>'''
;Usage 1: '''<code>var(''x''<sub>vector</sub>)</code>'''
;Result 1: The variance ''v'' of vector ''x''.  
;Result 1: The variance ''v'' of vector ''x''.  
:<code>''v'' = sum<sub>i = 0..nrow(''x'')-1</sub> ( (''x''<sub>i</sub>-avr(''x''))^2 ) / (nrow(''x'')-1)</code>
:<code>''v'' = sum( (''x''-avr(''x''))?^2 ) / (nrow(''x'')-1) = (''x''-avr(''x'')^2 / (ncol(''x'')-1)</code>
----
----
;Usage 2: '''<code>var(''x''<sub>vector</sub>, ''y''<sub>vector</sub>)</code>'''
;Usage 2: '''<code>var(''x''<sub>vector</sub>, ''y''<sub>vector</sub>)</code>'''

Revision as of 14:53, 8 April 2011

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) = (x-avr(x)^2 / (ncol(x)-1)

Usage 2
var(xvector, yvector)
Result 2
The covariance v of the vectors x and y.
v = sumi = 0..nrow(x) ( (xi-avr(x)) * (yi-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.
vi,j = sumk = 0..nrow(x) ( (xk,i-ai) * (xk,j-aj) ) / (nrow(x)-1) , with: i,j = 0..ncol(x)
The column averages ai=0..ncol(x) are computed as follows:
y not supplied ai = avr(x*,i)
yscalar ai = y
yvector ai = yi
See also
avr, dev, corr

<function list>

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