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Locally Weighted Regression

Select menu: Stats | Regression Analysis | Linear Models

The Locally weighted regression downdown list option fits a model based on one x-variate. The assumption in the modelling is that the locally, around any point, the regression surface can be approximated by a function from a particular class: polynomials of order 1 (linear) or 2 (quadratic).

Response variate

Specifies the name of the response (or y-) variate.

Explanatory variate

Specifies the name of the explanatory (or x-) variate.

Smooth using

Controls whether approximate degrees of freedom or a smoothing parameter are to be supplied.

Degrees of freedom

Specifies the degrees of freedom from which Genstat searches for the appropriate span to generate a smoothing model with the required degrees of freedom.

Smoothing parameter

Specifies the span to indicate what proportion of points are used to fit the regression model at each position.

Polynomial model

Specifies the polynomial model to be used. You can choose either Linear or Quadratic.

See also

  • Linear Regression for information on general options and other models
  • Options for choosing which results to display
  • Further Output for additional output subsequent to analysis
  • Saving Results for further analysis
  • Fitted Model for graphical display of the model
  • Model Checking to generate diagnostic plots for model checking
  • MODEL and FIT directives for fitting regression models using the command language
  • LOESS function for fitting locally weighted regression models
Updated on January 25, 2022

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