Smoothing |
The SmoothingCubicSplineBase type exposes the following members.
Methods| Name | Description | |
|---|---|---|
  | cubgcv | |
| CubicSplineCoefficients |
Calculate the spline coefficients y2(i) and y3(i) for a natural cubic
spline, given the abscissa x(i), the ordinate y(i), and the 1st
derivative y1(i).
(Inherited from CurveBase) |
| CubicSplineHorner |
Return the interpolation value P(u) for a piecewise cubic curve determined
by the abscissa vector x, the ordinate vector y, the 1st derivative
vector y1, the 2nd derivative vector y2, and the 3rd derivative vector y3,
using the Horner scheme.
(Inherited from CurveBase) |
| CubicSplineHorner1stDerivative | (Inherited from CurveBase) |
| Equals | Determines whether the specified object is equal to the current object. (Inherited from Object) |
 | Finalize | Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object) |
| GetCurvePoints |
Get curve points to draw an interpolation curve between the abscissa values xlo and xhi.
It calls the virtual methods MpCurveBase::GetXOfU() and GetYOfU() to obtain the
interpolation values. Note, that before method DrawCurve() can be called
the method Interpolate() must have been called. Otherwise, not interpolation
is available.
(Inherited from CurveBase) |
| GetHashCode | Serves as the default hash function. (Inherited from Object) |
| GetType | Gets the Type of the current instance. (Inherited from Object) |
| GetXOfU | (Overrides CurveBaseGetXOfU(Double)) |
| GetY1stDerivativeOfX | |
| GetYOfU | (Overrides CurveBaseGetYOfU(Double)) |
| GetYOfX | |
| Interpolate(IReadOnlyListDouble, IReadOnlyListDouble) |
Evaluates either a cross validated cubic spline (if ErrorStandardDeviation is negative,
or a smoothing cubic spline (if ErrorStandardDeviation is greater than or equal to zero).
(Overrides CurveBaseInterpolate(IReadOnlyListDouble, IReadOnlyListDouble)) |
| Interpolate(IReadOnlyListDouble, IReadOnlyListDouble, Double) | Evaluates either a cross validated cubic spline (standardDeviation set to a negative value), or a smoothing cubic spline (standardDeviation set to a non-negative value). |
| Interpolate(IReadOnlyListDouble, IReadOnlyListDouble, Double, IReadOnlyListDouble) | Evaluates either a cross validated cubic spline (standardDeviation set to a negative value), or a smoothing cubic spline (standardDeviation set to a non-negative value). |
| InterpolationKernel | |
| MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object) |
| NotExecutedException | |
| Parametrize |
Curve length parametrization. Returns the accumulated "distances"
between the points (x(i),y(i)) and (x(i+1),y(i+1)) in t(i+1)
for i = lo ... hi. t(lo) = 0.0 always.
(Inherited from CurveBase) |
| spcof1 | Calculates coefficients of a cubic smoothing spline from parameters calculated by subroutine spfit. |
| sperr1 | Calculates bayesian estimates of the standard errors of the fitted values of a cubic smoothing spline by calculating the diagonal elements of the influence matrix. |
| spfit1 | Fits a cubic smoothing spline to data with relative weighting dy for a given value of the smoothing parameter rho using an algorithm based on that of C.H.Reinsch (1967), Numer. Math. 10, 177-183. The trace of the influence matrix is calculated using an algorithm developed by M.F.hutchinson and F.R.de Hoog (Numer. Math., in press), enabling the generalized cross validation and related statistics to be calculated in order n operations. The arrays a, c, r and t are assumed to have been initialized by the subroutine spint. Overflow and underflow problems are avoided by using p=rho/(1 + rho) and q=1/(1 + rho) instead of rho and by scaling the differences x[i+1] - x[i] by avh. the values in df are assumed to have been scaled so that the sum of their squared values is n. The value in var, when it is non-negative, is assumed to have been scaled to compensate for the scaling of the values in df. The value returned in fun is an estimate of the true mean square when var is non-negative, and is the generalized cross validation when var is negative. |
| spint1 | Initializes the arrays c, r and t for one dimensional cubic smoothing spline fitting by subroutine spfit1. The values df(i) are scaled so that the sum of their squares is n and the average of the differences x(i+1) - x(i) is calculated in avh in order to avoid underflow and overflow problems in spfit1. This subroutine sets ier if elements of x are non-increasing, if n is less than 3, if ic is less than n-1 or if dy(i) is not positive for some i. |
| ToString | Returns a string that represents the current object. (Inherited from Object) |
See Also