Accession Number : ADA195302
Title : Smoothing Spatial Data by Estimating Mean Local Variance.
Descriptive Note : Technical rept.,
Corporate Author : NAVAL POSTGRADUATE SCHOOL MONTEREY CA
Personal Author(s) : Johnson, Laura D
PDF Url : ADA195302
Report Date : Apr 1988
Pagination or Media Count : 36
Abstract : A nearest neighbor nonparametric regression method is used to estimate air pollution levels at other than measured points. The method requires an appropriate smoother. Cross-validation is used to determine the appropriate smoother. An alternative method is introduced to determine an appropriate level of smoothing which involves minimizing mean local variance. Mean local variance is a function of the size of a circular window. It is minimized for two pollutants in Ohio, New York and Florida. The smoother obtained by cross-validation using Ohio's data is compared to that obtained by minimizing mean local variance. Keywords: Air quality; Sulfur dioxide; Suspended particulates; Statistical data; Pollution concentrations.
Descriptors : *AIR POLLUTION, *NONPARAMETRIC STATISTICS, *REGRESSION ANALYSIS, AIR QUALITY, DIOXIDES, FLORIDA, MEAN, NEW YORK, OHIO, PARTICULATES, POLLUTANTS, STATISTICAL DATA, SULFUR OXIDES, SUSPENDED SEDIMENTS, VARIATIONS
Subject Categories : Air Pollution and Control
Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE