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APPLICATION MSWR REGRESSION IN DETERMINING Pb AND Zn ANOMALIES IN MOGHANJEGH, NW IRAN AND COMPARE ITS RESULTS ITH CLASSIC REGRESSION TECHNIQUES

A. Habibnia, A. Hezarkhani

First published: 2007DOI pendingView metrics

Abstract

Regression analysis is a well-established method to correct for grain size differences in suites of sediments. However, distortion caused by the presence of outliers and imprecision in both variables can hinder many common regression models from performing adequately. Median sum of weighted residuals (MSWR) regression is strongly outlier-resistant and accounts for imprecision in both variables for each member of a dataset. In a case study of Ni and Pb normalization for a suite of stream sediments in NW Iran, the ability of MSWR regression to detect anomalies was compared to ordinary least squares, weighted least squares, least absolute deviation and least median of squares regression. MSWR regression not only revealed more anomalous samples than the other methods, but also was able to distinguish anomalies in samples at comparatively low heavy metal concentration. MSWR anomalies in Moghanjegh may be related to unknown mineralization.

Publication details

Title
APPLICATION MSWR REGRESSION IN DETERMINING Pb AND Zn ANOMALIES IN MOGHANJEGH, NW IRAN AND COMPARE ITS RESULTS ITH CLASSIC REGRESSION TECHNIQUES
Authors
A. Habibnia, A. Hezarkhani
Proceedings
7th International Scientific Conference - SGEM2007
Publisher
SGEM Scientific GeoConference
Year
2007
Pages
Not available yet
ISSN
1314-2704
ISBN
954-918181-2
Language
en
Publication type
Conference Paper
Keywords
Classic regressionMSWRRobust regression
References6

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  6. Ryan, T.P., 1997. Modern Regression Methods. John Wiley & Sons,Inc., New York.

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