This durable set of base routines, written in Fortran in the late 1970s, are widely used. They smooth just as a function of one predictor for data with normal errors or for data with long-tailed symmetric errors (robust fitting). Statistics for inference are not computed. S-Plus, R, Systat, XploRE, Gauss, and SAS have interfaces to LOWESS.
LOWESS base software
SAS macro from Michael Friendly.
LOWESS was introduced in Visual and Computational Considerations in Smoothing Scatterplots by Locally Weighted Fitting. W. S. Cleveland. In Computer Science and Statistics: Eleventh Annual Symposium on the Interface, pages 96-100. Institute of Statistics, North Carolina State University, Raleigh, North Carolina, 1978. Robust Locally Weighted Fitting and Smoothing Scatterplots. W. S. Cleveland. Journal of the American Statistical Association, 74:829-836, 1979.
Computational methods were developed in LOWESS: A Program for Smoothing Scatterplots by Robust Locally Weighted Fitting. W. S. Cleveland. The American Statistician, 35:54, 1981. and implemented in the above base software.
The base software is a collection of C and Fortran subroutines that carry out local fitting for normal and long-tailed distributions and for one or more predictors. It also computes the statistics for inferences. S-PLUS has a complete implementation of LOESS as part of its modeling language.
LOESS base software
User's manual in postscript from netlib.
LOESS was introduced in Locally-Weighted Fitting: An Approach to Fitting Analysis by Local Fitting. W. S. Cleveland and S. J. Devlin. Journal of the American Statistical Association, 83:596-610, 1988.
Computational methods were developed in Computational Methods for Local Fitting. W. S. Cleveland and E. Grosse. Statistics and Computing, 1:47-62, 1991, and implemented in the above base software.
The S-PLUS functions for LOESS are described in Statistical Models in S. W. S. Cleveland, E. Grosse, and M. Shyu, edited by J. Chambers and T. Hastie, 309-376, Chapman and Hall, 1992.
Clive Loader's marvelous base software, written in C, is by far the most ambitious. It computes fits and statistics for a wide range of distributions, including normal, long-tailed, binomial, exponential, and Poisson. It also computes density estimates. It can be used as stand-alone program with its own interface, or as a library in the S-PLUS or R systems. The code, documentation, and discussion are at
LOCFIT web site
LOCFIT (as well as the fundamentals, methods, and theory of smoothing) is described in Local Fitting and Likelihood. Clive R. Loader. Springer.
STL is a procedure, based on loess, for decomposing a seasonal time series into a seasonal and other components specified by the user. The base software is written in Fortran. S-PLUS has an interface.
STL base software from netlib.
STL was introduced in STL: A Seasonal-Trend Decomposition Procedure Based on Loess (with Discussion) . R. B. Cleveland, W. S. Cleveland, J. E. McRae, and I. Terpenning. Journal of Official Statistics, 6:3-73, 1990.