The LOESS Procedure
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Overview
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Getting Started
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Syntax
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Details
Missing Values Output Data Sets Data Scaling Direct versus Interpolated Fitting kd Trees and Blending Local Weighting Iterative Reweighting Specifying the Local Polynomials Smoothing Matrix Model Degrees of Freedom Statistical Inference and Lookup Degrees of Freedom Automatic Smoothing Parameter Selection Sparse and Approximate Degrees of Freedom Computation Scoring Data Sets ODS Table Names ODS Graphics
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Examples
- References
| Model Degrees of Freedom |
The approximate model degrees of freedom in a nonparametric fit is a number that is analogous to the number of free parameters in a parametric model. There are three commonly used measures of model degrees of freedom in nonparametric models. These criteria are as follows:
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A discussion of their properties can be found in Hastie and Tibshirani (1990). DF2 is also referred to as the "Equivalent Number of Parameters," and this is the name that PROC LOESS uses for DF2 when it appears in the "Fit Summary" table.