Programmer Guide/Command Reference/EVAL/corrfun: Difference between revisions
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;Usage: | ;Usage: | ||
:{|class="keinrahmen" | :{|class="keinrahmen" | ||
| | |<code>corrfun(''x''<sub>vector</sub> {, ''n'' {, ''scale''}})</code> | ||
| ... autocorrelation of ''x'' | | ... autocorrelation of ''x'' | ||
|- | |- | ||
| | |<code>corrfun(''x''<sub>vector</sub>, ''y''<sub>vector</sub> {, ''n'' {, ''scale''}})</code> | ||
| ... cross correlation of ''x'' and ''y'' | | ... cross correlation of ''x'' and ''y'' | ||
|} | |} | ||
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|} | |} | ||
;Result: The autocorrelation of the data vector ''x'' or the cross correlation function of the vectors ''x'' and ''y''. The result is a scalar (if ''n''=1) or a vector with ''n'' elements. | ;Result: The autocorrelation of the data vector ''x'' or the cross correlation function of the vectors ''x'' and ''y''. The result is a scalar (if ''n''=1) or a vector with ''n'' elements. | ||
;See also: [[../corr|corr]] | |||
[[../#Functions|<function list>]] | |||
Revision as of 10:28, 21 April 2011
Compute the autocorrelation or cross-correlation function.
- Usage
corrfun(xvector {, n {, scale}})... autocorrelation of x corrfun(xvector, yvector {, n {, scale}})... cross correlation of x and y
- x, y
- data vectors
- n
- the number of lags; 0 < n <
ncol(x)(default=ncol(x)/2) - scale
- specifies the scaling of the function:
scale=0 ... no scaling (default) scale=1 ... "biased", each lag i is scaled by the length of x ( 1/ncol(x))scale=2 ... "unbiased", each lag i is scaled by the number of correlated elements ( 1/(ncol(x)-i))
- Result
- The autocorrelation of the data vector x or the cross correlation function of the vectors x and y. The result is a scalar (if n=1) or a vector with n elements.
- See also
- corr
