Function"Variance with weights" of a one-dimensional distribution with respect to a pre-set value.
Syntax C/C++#include <VFstd.h>
float VF_varianceCwW( fVector X, fVector Wt, ui size, float C );
C++ VecObj#include <OptiVec.h>
T vector<T>::varianceCwW( const vector<T>& Wt, const T& C );
Pascal/Delphiuses VFstd;
function VF_varianceCwW( X, Wt:fVector; size:UIntSize; C:Single ): Single;
CUDA function C/C++#include <cudaVFstd.h>
int cudaVF_varianceCwW( float *h_RetVal, fVector d_X, fVector d_Wt, ui size, float C );
int cusdVF_varianceCwW( float *d_RetVal, fVector d_X, fVector d_Wt, ui size, float *d_C );
float VFcu_varianceCwW( fVector h_X, fVector h_Wt, ui size, float C );
CUDA function Pascal/Delphiuses VFstd;
function cudaVF_varianceCwW( var h_RetVal:Single; d_X, d_Wt:fVector; size:UIntSize; C:Single ): IntBool;
function cusdVF_varianceCwW( d_RetVal:PSingle; d_X, d_Wt:fVector; size:UIntSize; d_C:PSingle ): IntBool;
function VFcu_varianceCwW( h_X, h_Wt:fVector; size:UIntSize; C:Single ): Single;
Descriptionvar = (1 / sum( Wti )) * sum( Wti * (Xi - C)2 )
The weights need not be normalized.
Error handlingnone
Return valuevariance of the distribution.
See alsoVF_meanwW,   VF_varianceC,   VF_varianceVwW,   VF_linregress

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