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

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Compute the correlation coefficient or the correlcation matrix.
Compute the correlation coefficient or the correlcation matrix.
----
----
;Usage 1: '''<code>var(''x''<sub>vector</sub>, ''y''<sub>vector</sub>)</code>'''
;Usage 1: '''<code>corr(''x''<sub>vector</sub>, ''y''<sub>vector</sub>)</code>'''
;Result 1: The correlecation coefficient ''r'' (product-moment correlation) of the vectors ''x'' and ''y''.  
;Result 1: The correlecation coefficient ''r'' (product-moment correlation) of the vectors ''x'' and ''y''.  
:<code>''r'' = var(''x'', ''y'') / sqrt( var(''x'') * var(''y'') )</code>
:<code>''r'' = var(''x'', ''y'') / sqrt( var(''x'') * var(''y'') )</code>
----
----
;Usage 2: '''<code>var(''x''<sub>matrix</sub>)</code>'''
;Usage 2: '''<code>corr(''x''<sub>matrix</sub>)</code>'''
:'''<code>var(''x''<sub>matrix</sub>, ''y''<sub>scalar</sub>)</code>'''
:'''<code>corr(''x''<sub>matrix</sub>, ''y''<sub>scalar</sub>)</code>'''
:'''<code>var(''x''<sub>matrix</sub>, ''y''<sub>vector</sub>)</code>'''
:'''<code>corr(''x''<sub>matrix</sub>, ''y''<sub>vector</sub>)</code>'''
;Result 2: The correlation matrix ''r'' of the column vectors of ''x''.  
;Result 2: The correlation matrix ''r'' of the column vectors of ''x''.  
:<code>''r''[i,j] = var(''x[*,i]'', ''x''[*,j]) / sqrt( var(''x''[*,i]) * var(''x''[*,j]) ) , with: i,j = 0..ncol(''x'')-1</code>
:<code>''r''[i,j] = var(''x[*,i]'', ''x''[*,j]) / sqrt( var(''x''[*,i]) * var(''x''[*,j]) ) , with: i,j = 0..ncol(''x'')-1</code>

Revision as of 14:10, 8 April 2011

Compute the correlation coefficient or the correlcation matrix.


Usage 1
corr(xvector, yvector)
Result 1
The correlecation coefficient r (product-moment correlation) of the vectors x and y.
r = var(x, y) / sqrt( var(x) * var(y) )

Usage 2
corr(xmatrix)
corr(xmatrix, yscalar)
corr(xmatrix, yvector)
Result 2
The correlation matrix r of the column vectors of x.
r[i,j] = var(x[*,i], x[*,j]) / sqrt( var(x[*,i]) * var(x[*,j]) ) , with: i,j = 0..ncol(x)-1
If the argument y is supplied, it is used as column average like for the computation of the covariance matrix.
See also
avr, dev, var, corrfun

<function list>

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