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Robust Graphical Methods for Diagnosing Trend in Irregularly Spaced Water Quality Time Series by Byron A. Bodo is a Environmental Science article available to read on EtoBox.

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Graphical methods can play an important role in the reliable assessment of trends in typically ill behaved river quality data series both as diagnostic tools and as visual corroborative evidence when assumptions required for formal statistical tests are not met. Robust, graphically-oriented trend diagnosis procedures are presented for data series characterized by nonnormal populations, uneven time spacing, nonmonotonic trend and other factors which can create serious problems for standard parametric time series methods. Cleveland's robust locally weighted regression (RLWR) developed for investigating nonlinearity in x-y scatterplots is adapted as a robust/resistant smoothing filter for the analysis of irregular time series comprising quantitative observations. Low powered RLWR trend lines reveal temporally local phenomena, e.g. abrupt jumps (often associated with point source impacts) and periodicities, while higher powered RLWR yields smooth lines characterizing medium and longer term trends. Simple variants of Tukey smoothing concepts are developed for series with censored observations. Applications to Ontario river quality series reveal that graphical evidence is frequently suff

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Author

Byron A. Bodo

Publisher

Springer; Springer-Verlag; Kluwer Academic Publishers; Springer Science and Business Media LLC; Publons; Society for Mining, Metallurgy and Exploration Inc. (ISSN 0167-6369)

Published

1989

Language

EN

Field

Environmental Science (Physical Sciences)