FunctionBasis.LeastSquaresFit Method

Definition

Namespace: Extreme.Mathematics.Curves
Assembly: Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.23

Overload List

LeastSquaresFit(Vector<Double>, Vector<Double>)	Gets the least squares fit of target data in terms of the components of the FunctionBasis.
LeastSquaresFit(Double[], Double[], Double[])	Gets the least squares fit of target data in terms of the components of the FunctionBasis.
LeastSquaresFit(Double[], Double[], Int32)	Gets the least squares fit of target data in terms of the components of the FunctionBasis.
LeastSquaresFit(Vector<Double>, Vector<Double>, Vector<Double>)	Gets the least squares fit of target data in terms of the components of the FunctionBasis.

FunctionBasis.LeastSquaresFit(Vector<Double>, Vector<Double>)

Gets the least squares fit of target data in terms of the components of the FunctionBasis.

public virtual LinearCombination LeastSquaresFit(
	Vector<double> xValues,
	Vector<double> yValues
)

Visual Basic

Public Overridable Function LeastSquaresFit ( 
	xValues As Vector(Of Double),
	yValues As Vector(Of Double)
) As LinearCombination

C++/CLI

public:
virtual LinearCombination^ LeastSquaresFit(
	Vector<double>^ xValues, 
	Vector<double>^ yValues
)

abstract LeastSquaresFit : 
        xValues : Vector<float> * 
        yValues : Vector<float> -> LinearCombination 
override LeastSquaresFit : 
        xValues : Vector<float> * 
        yValues : Vector<float> -> LinearCombination

Parameters

xValues Vector<Double>: A vector containing the data points for the fit.
yValues Vector<Double>: A vector containing the data values corresponding to the data points in xValues.

Return Value

>LinearCombination
A LinearCombination that is the least squares fit of the data in terms of this FunctionBasis.

Exceptions

ArgumentNullException	xValues is null. -or- yValues is null.
TotalLossOfPrecisionException	The solution of the least squares problem could not be found because roundoff error caused a total loss of precision.
DimensionMismatchException	The xValues and yValues do not have the same length.
ArgumentException	The number of data points is less than the number of basis functions.

FunctionBasis.LeastSquaresFit(Double[], Double[], Double[])

Gets the least squares fit of target data in terms of the components of the FunctionBasis.

public virtual LinearCombination LeastSquaresFit(
	double[] xValues,
	double[] yValues,
	double[] weights
)

Visual Basic

Public Overridable Function LeastSquaresFit ( 
	xValues As Double(),
	yValues As Double(),
	weights As Double()
) As LinearCombination

C++/CLI

public:
virtual LinearCombination^ LeastSquaresFit(
	array<double>^ xValues, 
	array<double>^ yValues, 
	array<double>^ weights
)

abstract LeastSquaresFit : 
        xValues : float[] * 
        yValues : float[] * 
        weights : float[] -> LinearCombination 
override LeastSquaresFit : 
        xValues : float[] * 
        yValues : float[] * 
        weights : float[] -> LinearCombination

Parameters

xValues Double[]: A Double array containing the data points for the fit.
yValues Double[]: A Double array containing the data values corresponding to the data points. in xValues.
weights Double[]: A Double array containing the weights to assign to the residual error corresponding to the data values in yValues.

Return Value

>LinearCombination
A LinearCombination that is the least squares fit of the data in terms of this FunctionBasis.

Exceptions

ArgumentNullException	xValues is null. -or- yValues is null.
TotalLossOfPrecisionException	The solution of the least squares problem could not be found because roundoff error caused a total loss of precision.
DimensionMismatchException	The xValues and yValues do not have the same length.
ArgumentException	The number of data points is less than the number of basis functions.

FunctionBasis.LeastSquaresFit(Double[], Double[], Int32)

Gets the least squares fit of target data in terms of the components of the FunctionBasis.

public virtual LinearCombination LeastSquaresFit(
	double[] xValues,
	double[] yValues,
	int numberOfDataPoints
)

Visual Basic

Public Overridable Function LeastSquaresFit ( 
	xValues As Double(),
	yValues As Double(),
	numberOfDataPoints As Integer
) As LinearCombination

C++/CLI

public:
virtual LinearCombination^ LeastSquaresFit(
	array<double>^ xValues, 
	array<double>^ yValues, 
	int numberOfDataPoints
)

abstract LeastSquaresFit : 
        xValues : float[] * 
        yValues : float[] * 
        numberOfDataPoints : int -> LinearCombination 
override LeastSquaresFit : 
        xValues : float[] * 
        yValues : float[] * 
        numberOfDataPoints : int -> LinearCombination

Parameters

xValues Double[]: A Double array containing the data points for the fit.
yValues Double[]: A Double array containing the data values corresponding to the data points in xValues.
numberOfDataPoints Int32: The number of actual data points.

Return Value

>LinearCombination
A LinearCombination that is the least squares fit of the data in terms of this FunctionBasis.

Remarks

Use this method to calculate a LinearCombination of the basis functions in this instance through a set of points using the least squares method.

Only the first numberOfDataPoints values in xValues and yValues are used.

Exceptions

ArgumentNullException

xValues is null.

-or-

yValues is null.

ArgumentOutOfRangeException

numberOfDataPoints is less than the number of basis functions.

-or-

numberOfDataPoints is greater than the length of xValues

-or-

numberOfDataPoints is greater than the length of yValues

TotalLossOfPrecisionException

The solution of the least squares problem could not be found because roundoff error caused a total loss of precision.

FunctionBasis.LeastSquaresFit(Vector<Double>, Vector<Double>, Vector<Double>)

Gets the least squares fit of target data in terms of the components of the FunctionBasis.

public virtual LinearCombination LeastSquaresFit(
	Vector<double> xValues,
	Vector<double> yValues,
	Vector<double> weights
)

Visual Basic

Public Overridable Function LeastSquaresFit ( 
	xValues As Vector(Of Double),
	yValues As Vector(Of Double),
	weights As Vector(Of Double)
) As LinearCombination

C++/CLI

public:
virtual LinearCombination^ LeastSquaresFit(
	Vector<double>^ xValues, 
	Vector<double>^ yValues, 
	Vector<double>^ weights
)

abstract LeastSquaresFit : 
        xValues : Vector<float> * 
        yValues : Vector<float> * 
        weights : Vector<float> -> LinearCombination 
override LeastSquaresFit : 
        xValues : Vector<float> * 
        yValues : Vector<float> * 
        weights : Vector<float> -> LinearCombination

Parameters

xValues Vector<Double>: A vector containing the data points for the fit.
yValues Vector<Double>: A vector containing the data values corresponding to the data points in xValues.
weights Vector<Double>: A vector containing the weights to assign to the residual error corresponding to the data values in yValues.

Return Value

>LinearCombination
A LinearCombination that is the least squares fit of the data in terms of this FunctionBasis.

Exceptions

ArgumentNullException	xValues is null. -or- yValues is null.
TotalLossOfPrecisionException	The solution of the least squares problem could not be found because roundoff error caused a total loss of precision.
DimensionMismatchException	The xValues and yValues do not have the same length.
ArgumentException	The number of data points is less than the number of basis functions.

FunctionBasis.LeastSquaresFit Method

Definition

Overload List

FunctionBasis.LeastSquaresFit(Vector<Double>, Vector<Double>)

Parameters

Return Value

Exceptions

FunctionBasis.LeastSquaresFit(Double[], Double[], Double[])

Parameters

Return Value

Exceptions

FunctionBasis.LeastSquaresFit(Double[], Double[], Int32)

Parameters

Return Value

Remarks

Exceptions

FunctionBasis.LeastSquaresFit(Vector<Double>, Vector<Double>, Vector<Double>)

Parameters

Return Value

Exceptions

See Also

Reference