Loess1D

This class is returned from the loess1D function and holds the state of a loess regression with one predictor variable.

final

class Loess1D {

double predict(double point, int robustness = 0);

void computeRobustWeights(int robustness, TaskPool pool = null);

const(double)[] predictions(int robustness, TaskPool pool = null);

int degree [@property getter];

const(double)[] x [@property getter];

const(double)[] y [@property getter];

}

Members

Functions

computeRobustWeights void computeRobustWeights(int robustness, TaskPool pool = null): Compute the weights for robust loess, for all robustness levels <= the robustness parameter. This computation is embarrassingly parallel, so if a TaskPool is provided it will be parallelized.
predict double predict(double point, int robustness = 0): Predict the value of y when x == point, using robustness iterations of the biweight procedure outlined in the reference to make the estimates more robust.
predictions const(double)[] predictions(int robustness, TaskPool pool = null): Obtain smoothed predictions of y at the values of x provided on creation of this object, for the given level of robustness. Evaluating these is computationally expensive and may be parallelized by providing a TaskPool object.

Properties

degree int degree [@property getter]: The polynomial degree for the local regression.
x const(double)[] x [@property getter]: The x values provided on object creation.
y const(double)[] y [@property getter]: The y values provided on object creation.

Meta

Source

See Implementation