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Published in:
2007 | OriginalPaper | Chapter
Generalized linear models for geostatistical data
Published in: Model-based Geostatistics
Publisher: Springer New York
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In the classical setting of independently replicated data, the generalized linear model (GLM) as introduced by Nelder and Wedderburn (1972) provides a unifying framework for regression modelling of continuous or discrete data. The original formulation has since been extended, in various ways, to accommodate dependent data. In this chapter we enlarge on the brief discussion of Section 1.4 to consider extensions of the classical GLM which are suitable for geostatistical applications.