Record Display for the EPA National Library Catalog

RECORD NUMBER: 32 OF 209

OLS Field Name OLS Field Data
Main Title Cubic Spline Smoothing: A Useful Tool for Curve Estimation.
Author DeHaan, M. S. ;
CORP Author Northrop Services, Inc., Corvallis, OR.;Corvallis Environmental Research Lab., OR.
Year Published 1988
Report Number EPA-68-03-3246; EPA/600/D-88/082;
Stock Number PB88-214796
Additional Subjects Curve fitting ; Regression analysis ; Least squares method ; Polynomials ; Mathematical prediction ; Spline functions ; Computer software
Holdings
Library Call Number Additional Info Location Last
Modified
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Status
NTIS  PB88-214796 Most EPA libraries have a fiche copy filed under the call number shown. Check with individual libraries about paper copy. NTIS 09/04/1988
Collation 10p
Abstract
Data analysis frequently involves fitting curves to data. Often the investigator has no idea what the underlying functional relationship is and ordinary functions or polynomials fit poorly. This is especially common with experimental data that has a lot of noise and/or measurement error in it. In these cases, spline smoothing can be used to estimate and fit curves with excellent results. Nonparametric cubic spline smoothing is a remarkably accurate and widely applicable approach to curve estimation that has been inexplicably underutilized. This powerful tool can be used in the exploratory, descriptive, and predictive stages of bivariate data analysis. Many examples of curve fitting using spline smoothing are given. Smoothing splines are compared to several other common methods of curve fitting. Methods are detailed for implementing spline smoothing on SAS software.