DoubleBisquareWeightingFunction Class 
Namespace: CenterSpace.NMath.Core
The DoubleBisquareWeightingFunction type exposes the following members.
Name  Description  

DoubleBisquareWeightingFunction 
Constructs an instance of DoubleBisquareWeightingFunction with
the default tuning factor.
 
DoubleBisquareWeightingFunction(Double) 
Constructs an instance of DoubleBisquareWeightingFunction with
the given tuning factor.
 
DoubleBisquareWeightingFunction(DoubleBisquareWeightingFunction) 
Copy constructor. Creates an instance of DoubleBisquareWeightingFunction
that is a deep copy of other.
 
DoubleBisquareWeightingFunction(DoubleMatrix) 
Constructs an instance of DoubleBisquareWeightingFunction
for the given matrix with
the default tuning factor.
 
DoubleBisquareWeightingFunction(DoubleMatrix, Double) 
Constructs a DoubleBisquareWeightingFunction for
the specified matrx and tuning factor.

Name  Description  

TuningConstant 
Gets and sets the tuning constant.
(Inherited from DoubleLeastSqWeightingFunction.) 
Name  Description  

AdjustedResiduals 
Returns a vector of adjusted residuals for the weighted least
squares problem:
Ax = b.
(Inherited from DoubleLeastSqWeightingFunction.)  
Clone 
Creates a deep copy of this weighting.
(Overrides DoubleLeastSqWeightingFunctionClone.)  
GetWeights 
Computes the bisquare weights for the residuals using the formula:
w(r) = (1  r^2)^2 if r is less than 1 and
w(r) = 0 if r is greater or equal to 1.
Here r is the adjusted redisuals from the AdjustedResidual
function of the base class DoubleLeastSqWeightingFunction.
(Overrides DoubleLeastSqWeightingFunctionGetWeights(DoubleVector, DoubleVector).)  
Initialize 
Performs initialization of the weighting function based on the matrix
A in the weighted least squares problem:
Ax  b.
(Inherited from DoubleLeastSqWeightingFunction.)  
MedianAbsDeviation 
Returns the Mean Absolute Deviation of a vector of values.
The mean absolute deviation is an estimate of the standard
deviation of the vector of residuals normalized to make the
estimate unbiased for the normal distribution.
(Inherited from DoubleLeastSqWeightingFunction.) 
Name  Description  

adjFactor_ 
Adjustment factor used in computing the adjusted residuals. It is given
by the formula:
1.0 / sqrt(1  h). Where,
h is the vector of leverage values. The leverage values are the
main diagonal of the hat matrix H = A((A'A)^1)A'.
(Inherited from DoubleLeastSqWeightingFunction.)  
cols_ 
Number of columns in the matrix A in the least squares problem.
Ax = b.
(Inherited from DoubleLeastSqWeightingFunction.)  
DEFAULT_TUNING_FACTOR 
Default value for the bisquare weighting tuning factor. If the response is normally
distributed, the default tuning factor
gives coefficient estimates that are approximately 95% as statistically
efficient as the ordinary least squares estimates.
 
rows_ 
Number of rows in the matrix A in the least squares problem.
Ax = b.
(Inherited from DoubleLeastSqWeightingFunction.)  
tuningConstant_ 
Tuning constant used in the weighting function. Implementing classes
should provide this value.
(Inherited from DoubleLeastSqWeightingFunction.) 