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Resampling Methods in Generalized Linear Models Useful in Environmetrics

โœ Scribed by Herwig Friedl; Ernst Stadlober

Publisher
John Wiley and Sons
Year
1997
Tongue
English
Weight
208 KB
Volume
8
Category
Article
ISSN
1180-4009

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โœฆ Synopsis

Generalized linear models are important tools for analysing relationships between binary, count or continuous response variables and predictors with ยฎxed eects. In this paper we present a survey on bootstrap methods based on (extended) quasi-likelihood assumptions. We discuss two approaches: one-step residual resampling and score resampling to estimate the variability of functions in the linear parameters of the model, and an iterative procedure which allows us to deยฎne replicates of the dependent variate. With the latter we are able to estimate non-linear parameters in the variance function and to compare non-nested models. The power of these resampling schemes is illustrated by air sampler data concentrating on the number of bacteria colonies observed at outdoor sites in the area of Graz.

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