Annoyance from Multiple Transportation Noise: Statistical Models and Outlier Detection

S. Kuhnt; C. Schürmann; B. Griefahn

doi:10.1055/s-0038-1633908

Methods of Information in Medicine, Table of Contents

Methods Inf Med 2004; 43(05): 510-515
DOI: 10.1055/s-0038-1633908

Original Article

Schattauer GmbH

Annoyance from Multiple Transportation Noise: Statistical Models and Outlier Detection

Authors

S. Kuhnt

¹Department of Statistics, University of Dortmund, Dortmund, Germany
C. Schürmann

¹Department of Statistics, University of Dortmund, Dortmund, Germany
B. Griefahn

²Institute for Occupational Physiology at the University of Dortmund, Dortmund, Germany

Abstract

Summary

Objective: Statistical models for the annoyance from multiple transportation noise are needed to understand and predict the annoyance resulting from specific noise exposures.

Methods: Models from the class of generalized linear models are suggested and discussed. Observations which are not well explained by the considered model are regarded as outliers. Outlier detection methods are applied to the data modelled by robust estimates using different link functions.

Results: The discussed methods are applied to data from a laboratory experiment using generalized linear models. While considering outliers, a generalized linear model with a complementary log-log link is found to be a good choice in modelling the exposure-response relationship between noise levels and annoyance.

Keywords

Generalized linear models - transportation noise - outliers - link function

Full Text

References

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