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
