FunctionLinear correlation coefficient between two distributions
Syntax C/C++#include <VFstd.h>
float VF_corrcoeff( fVector X, fVector Y, ui size, float Xmean, float Ymean );
C++ VecObj#include <OptiVec.h>
T vector<T>::corrcoeff( const vector<T>& Y, T Xmean, T Ymean );
Pascal/Delphiuses VFstd;
function VF_corrcoeff( X, Y:fVector; size:UIntSize; Xmean, Ymean:Single ): Single;
CUDA function C/C++#include <cudaVFstd.h>
int cudaVF_corrcoeff( ui *h_RetVal, fVector d_X, fVector d_Y, ui size, float Xmean, float Ymean );
int cusdVF_corrcoeff( ui *d_RetVal, fVector d_X, fVector d_Y, ui size, float *d_Xmean, float *d_Ymean );
float VFcu_corrcoeff( fVector h_X, fVector h_Y, ui size, float Xmean, float Ymean );
CUDA function Pascal/Delphiuses VFstd;
function cudaVF_corrcoeff( var h_RetVal:Single; d_X, d_Y:fVector; size:UIntSize; Xmean, Ymean:Single ): IntBool;
function cusdVF_corrcoeff( d_RetVal:PSingle; d_X, d_Y:fVector; size:UIntSize; d_Xmean, d_Ymean:PSingle ): IntBool;
procedure VFcu_corrcoeff( h_X, h_Y:fVector; size:UIntSize; Xmean, Ymean:Single );
DescriptionThe linear correlation coefficient ("Pearson's r") takes on values between −1.0 and +1.0. The mean values of both distributions must be known. They are passed to VF_corrcoeff as the parameters Xmean and Ymean.
Example C/C++r = VF_corrcoeff( X, Y, n, VF_mean( X, n ), VF_mean( Y, n ) );
Return valuelinear correlation coefficient r
See alsoVF_mean,   VF_varianceV,   VF_linregress

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