Function"Variance with weights" between two one-dimensional distributions.
Syntax C/C++#include <VFstd.h>
float VF_varianceVwW( fVector X, fVector Y, fVector Wt, ui size );
C++ VecObj#include <OptiVec.h>
T vector<T>::varianceVwW( const vector<T>& Y, const vector<T>& Wt );
Pascal/Delphiuses VFstd;
function VF_varianceVwW( X, Y, Wt:fVector; size:UIntSize ):
CUDA function C/C++#include <cudaVFstd.h>
int cudaVF_varianceVwW( float *h_RetVal, fVector X, fVector Y, fVector d_Wt, ui size );
int cusdVF_varianceVwW( float *d_RetVal, fVector X, fVector Y, fVector d_Wt, ui size );
float VFcu_varianceVwW( fVector h_X, fVector h_Y, fVector h_Wt, ui size );
CUDA function Pascal/Delphiuses VFstd;
function cudaVF_varianceVwW( var h_RetVal:Single; d_X, d_Y, d_Wt:fVector; size:UIntSize ): IntBool;
function cusdVF_varianceVwW( d_RetVal:PSingle; d_X, d_Y, d_Wt:fVector; size:UIntSize ): IntBool;
function VFcu_varianceVwW( h_X, h_Y, h_Wt:fVector; size:UIntSize ): Single;
Descriptionvar = (1 / sum(Wti)) * sum( Wti * (Xi - Yi)2 )
The weights need not be normalized.
Error handlingnone
Return valueweighted variance
See alsoVF_meanwW,   VF_chi2,   VF_varianceV,   VF_varianceCwW,   VF_linregress

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