Smoothing |
The SmoothingCubicSpline type exposes the following members.
Properties| Name | Description | |
|---|---|---|
 | CalculateStandardErrorEstimates |
If true, standard error estimates are calculated and provided in ErrorEstimate.
(Inherited from SmoothingCubicSplineBase) |
| CheckArguments |
If true, the array given as arguments are checked.
(Inherited from SmoothingCubicSplineBase) |
| Coefficient0 |
Returns the spline coefficient of order 0. This are the splined y values at the positions given by x.
(Inherited from SmoothingCubicSplineBase) |
| Coefficient1 |
Returns the spline coefficient of order 1 (linear term).
(Inherited from SmoothingCubicSplineBase) |
| Coefficient2 |
Returns the spline coefficient of order 2 (quadratic term).
(Inherited from SmoothingCubicSplineBase) |
| Coefficient3 |
Returns the spline coefficient of order 2 (cubic term).
(Inherited from SmoothingCubicSplineBase) |
| CombineNeighbouringPoints |
If true, points with x values that are very similar are combined into one point, which helds the average value of x and y
(Inherited from SmoothingCubicSplineBase) |
| ErrorEstimate |
Returns the error estimates of the y points.
(Inherited from SmoothingCubicSplineBase) |
| ErrorStandardDeviation |
If the error standard deviation of the provided points is unknown, set this value to -1. Then a cross validating cubic spline is fitted to the data.
If the error standard deviation is known and is equal for all points, set this value to the error standard deviation of the points.
If the error standard deviation is known and different for each point, set this value to 1, and provide the error standard deviation for each point
by calling Interpolate(IReadOnlyListDouble, IReadOnlyListDouble, Double, IReadOnlyListDouble).
(Inherited from SmoothingCubicSplineBase) |
| EstimatedDegreesOfFreedom |
Estimate of the number of degrees of
freedom of the residual sum of squares
which reduces to the usual value of n-2
when a least squares regression line
was calculated.
(Inherited from SmoothingCubicSplineBase) |
| EstimatedErrorVariance |
Estimate of the error variance.
The value coincides with the output value of var if var is negative on input.
It is calculated with the unscaled values of the df[i] to facilitate
comparisons with a priori variance estimates.
(Inherited from SmoothingCubicSplineBase) |
| EstimatedTrueMeanSquareError |
Estimate of the true mean square error at the data points.
(Inherited from SmoothingCubicSplineBase) |
| GeneralizedCrossValidation |
Generalized cross validation.
(Inherited from SmoothingCubicSplineBase) |
| MeanSquareOfInputStandardDeviation |
Mean square value of the standard deviations in dy[i] (if they were provided).
The values of GeneralizedCrossValidation, MeanSquareResidual and EstimatedTrueMeanSquareError
are calculated with the dy[i] scaled to have a mean square value 1.
The unscaled values of GeneralizedCrossValidation, MeanSquareResidual and EstimatedTrueMeanSquareError
may be calculated by dividing by this value.
(Inherited from SmoothingCubicSplineBase) |
| MeanSquareResidual |
Mean square residual.
(Inherited from SmoothingCubicSplineBase) |
| SmoothingParameter |
Smoothing parameter = rho/(rho+1), that varies between 0 (not smoothed) and 1 (full smoothed).
If the value is 0 (rho=0) an interpolating natural cubic spline has been calculated.
If the value is 1 (rho=infinite) a least squares regression line has been calculated.
(Inherited from SmoothingCubicSplineBase) |
| Smoothness | Get/sets the smoothness parameter. Must be in the interval [0,Infinity], where a value of 0 means no smoothing (evaluation of a cubic spline), while a value of Infinity means evaluation of a regression. |
See Also