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