Annoyance from multiple transportation noise: Statistical models and outlier detection
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.
transportation noise outliers generalized linear models link function