Namespace:
Imsl.Math
Assembly:
ImslCS (in ImslCS.dll) Version: 6.5.0.0
Syntax
C# |
---|
[SerializableAttribute] public class BsLeastSquares : BSpline |
Visual Basic (Declaration) |
---|
<SerializableAttribute> _ Public Class BsLeastSquares _ Inherits BSpline |
Visual C++ |
---|
[SerializableAttribute] public ref class BsLeastSquares : public BSpline |
Remarks
Let's make the identifications
n = xData.Length
x = xData
f = yData
m = nCoef
k = order
For convenience, we assume that the sequence x is increasing, although the class does not require this.
By default, k = 4, and the knot sequence we select equally
distributes the knots through the distinct .
In particular, the m + k knots will be generated in
with k knots stacked at each of
the extreme values. The interior knots will be equally spaced in the
interval.
Once knots and weights w are
determined, then the spline least-squares fit to the data is computed by
minimizing over the linear coefficients
![\sum_{i=0}^{n-1}
{w_i\biggl[f_i-\sum_{j=1}^{m}{a_jB_j(x_i)}\biggr]^2}](eqn/eqn_0532.png)
where the are a (B-spline) basis
for the spline subspace.
This algorithm is based on the routine L2APPR by deBoor (1978, p. 255).