Abstract
A method is presented for evaluation of normalising constants in GLIM. Based on a weighted Poisson model and suitably chosen dummy weights a wide variety of normalising constant models can be fitted. Examples are given of an LR test for ‘von Misesness’ equivalent to Cox's (1975) score test, the estimation of κ for a Fisher distribution, and parameter estimation for a spatial Heterogeneous Poisson Process.
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