- (Cleveland, 1979) ⇒ William S. Cleveland. (1979). “Robust Locally Weighted Regression and Smoothing Scatterplots.” In: Journal of the American Statistical Association 1979, (74:368). doi:10.2307/2286407
- ~4805 http://scholar.google.com/scholar?q=%22Robust+Locally+Weighted+Regression+and+Smoothing+Scatterplots%22+1979
The visual information on a scatterplot can be greatly enhanced, with little additional cost, by computing and plotting smoothed points. Robust locally weighted regression is a method for smoothing a scatterplot, (xi, yi), i = 1, ⋯, n, in which the fitted value at xk is the value of a polynomial fit to the data using weighted least squares, where the weight for (xi, yi) is large if xi is close to xk and small if it is not. A robust fitting procedure is used that guards against deviant points distorting the smoothed points. Visual, computational, and statistical issues of robust locally weighted regression are discussed. Several examples, including data on lead intoxication, are used to illustrate the methodology.
|Author||William S. Cleveland +|
|journal||Journal of the American Statistical Association +|
|title||Locally Weighted Regression and Smoothing Scatterplots +|