| BsLeastSquares Class |
Namespace: Imsl.Math
The BsLeastSquares type exposes the following members.
| Name | Description | |
|---|---|---|
| BsLeastSquares(Double, Double, Int32) |
Constructs a least squares B-spline approximation to the given data
points.
| |
| BsLeastSquares(Double, Double, Int32, Int32) |
Constructs a least squares B-spline approximation to the given data
points.
| |
| BsLeastSquares(Double, Double, Int32, Int32, Double, Double) |
Constructs a least squares B-spline approximation to the given data
points.
|
| Name | Description | |
|---|---|---|
| Derivative(Double) |
Returns the value of the first derivative of the B-spline at a point.
(Inherited from BSpline.) | |
| Derivative(Double, Int32) |
Returns the value of the derivative of the B-spline at a point.
(Inherited from BSpline.) | |
| Derivative(Double, Int32) |
Returns the value of the derivative of the B-spline at each point of
an array.
(Inherited from BSpline.) | |
| Equals | Determines whether the specified object is equal to the current object. (Inherited from Object.) | |
| Eval(Double) |
Returns the value of the B-spline at a point.
(Inherited from BSpline.) | |
| Eval(Double) |
Returns the value of the B-spline at each point of an array.
(Inherited from BSpline.) | |
| Finalize | Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object.) | |
| GetHashCode | Serves as a hash function for a particular type. (Inherited from Object.) | |
| GetKnots |
Returns a copy of the knot sequence.
(Inherited from BSpline.) | |
| GetSpline |
Returns a Spline representation of the B-spline.
(Inherited from BSpline.) | |
| GetType | Gets the Type of the current instance. (Inherited from Object.) | |
| Integral |
Returns the value of an integral of the B-spline.
(Inherited from BSpline.) | |
| MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object.) | |
| ToString | Returns a string that represents the current object. (Inherited from Object.) |
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 ![]()
where the
are a (B-spline) basis
for the spline subspace.
This algorithm is based on the routine L2APPR by deBoor (1978, p. 255).