loess¶

Purpose¶

Computes coefficients of locally weighted regression.

Format¶

{ yhat, ys, xs } = loess(depvar, indvars)¶

Parameters:

depvar (Nx1 vector) – dependent variable.
indvars (NxK matrix) – independent variables.

Returns:

yhat (Nx1 vector) – predicted depvar given indvars.
ys (_loess_numEvalx1 vector) – ordinate values given abscissae values in xs.
xs (_loess_numEvalx1 vector) – equally spaced abscissae values.

Global Input¶

_loess_Span	scalar, degree of smoothing. Must be greater than 2/N. Default = .67777.
_loess_NumEval	scalar, number of points in ys and xs. Default = 50.
_loess_Degree	scalar, if 2, quadratic fit, otherwise linear. Default = 1.
_loess_WgtType	scalar, type of weights. If 1, robust, symmetric weights, otherwise Gaussian. Default = 1.
__output	scalar, if 1, iteration information and results are printed, otherwise nothing is printed.

Examples¶

// Load dataset
data = loadd("lowess1.dta", "h1 + depth");

// Define independent variable
depvar = data[., 1];

// Defined dependent variable
indvars = data[., 2];

{ yhat, ys, xs } = loess(depvar, indvars);

Remarks¶

Based on Cleveland, William S. “Robust Locally Weighted Regression and Smoothing Scatterplots.” JASA, Vol. 74, 1979, 829-836.

Source¶

loess.src

loessmt

loglog