Difference between revisions of "SampleCorrelation"

Revision as of 22:21, 18 January 2016

SampleCorrelation(X, I, J, R)

Returns a correlation matrix based on data in «X», where each data point is a vector indexed by «I», and the entries in the correlation matrix are the pair-wise correlations of the columns of data. A second index, «J», of size identical to «I», is required in order to index the 2-dimensional result.

Syntax:

SampleCorrelation(X : array[I, R]; I, J, R: IndexType)

Library

Multivariate Distributions.ana

Notes

You can also use the built-in function Correlation to compute a correlation matrix. The built-in function is actually more flexible since it can also be used with sample weighting. The equivalent of SampleCorrelation(X, I, J, R) is:

Correlation(X, X[I = J], R)

@@ Line 2: / Line 2: @@
 [[Category:Doc Status C]] <!-- For Lumina use, do not change -->
-= SampleCorrelation(X : array[I,R] ; I,J,R : IndexType) =
+== SampleCorrelation(X, I, J, R) ==
+Returns a correlation matrix based on data in «X», where each data point is a vector indexed by «I», and the entries in the correlation matrix are the pair-wise correlations of the columns of data.  A second index, «J», of size identical to «I», is required in order to index the 2-dimensional result.
-Returns a correlation matrix based on data in X, where each data point is a vector indexed by I, and the entries in the correlation matrix are the pair-wise correlations of the columns of data.  A second index, J, of size identical to I, is required in order to index the 2-dimensional result.
+[[Syntax]]:
+:[[SampleCorrelation]](X : array[I, R]; I, J, R: IndexType)
-= Library =
+== Library ==
+<code>Multivariate Distributions.ana</code>
-Multivariate Distributions.ana
+== Notes ==
+You can also use the built-in function [[Correlation]] to compute a correlation matrix.  The built-in function is actually more flexible since it can also be used with sample weighting.  The equivalent of [[SampleCorrelation]](X, I, J, R) is:
-= Notes =
+:<code>Correlation(X, X[I = J], R)</code>
-Note: You can also use the built-in function [[Correlation]] to compute a correlation matrix.  The built-in function is actually more flexible since it can also be used with sample weighting.  The equivalent of SampleCorrelation(X,I,J,R) is:
- [[Correlation]]( X, X[I=J], R )
-= See Also =
+== See Also ==
 * [[SampleCovariance]]
 * [[Correlation]]