VF_corrcoeff VD_corrcoeff VE_corrcoeff
 Function Linear correlation coefficient between two distributions
 Syntax C/C++ #include float VF_corrcoeff( fVector X, fVector Y, ui size, float Xmean, float Ymean ); C++ VecObj #include T vector::corrcoeff( const vector& Y, T Xmean, T Ymean ); Pascal/Delphi uses VFstd; function VF_corrcoeff( X, Y:fVector; size:UIntSize; Xmean, Ymean:Single ): Single;
 CUDA function C/C++ #include 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/Delphi uses 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 );
 Description The 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 value linear correlation coefficient r