GLIM and normalising constant models in spatial and directional data analysis

DOI10.1016/0167-9473(92)90140-BzbMath0800.62008OpenAlexW2036170654MaRDI QIDQ1330527

Andrew B. Lawson

Publication date: 21 July 1994

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-9473(92)90140-b

zbMATH Keywords

spatialintegrationPoisson modelnumericalvon MisesFisherGLIMdirectionalnormalising constants

Mathematics Subject Classification ID

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Cites Work

• Smoothing counting process intensities by means of kernel functions
• On the homogeneous planar Poisson point process
• Statistical Analysis of Spherical Data
• Efficient Simulation of the von Mises Distribution
• Approximating Point Process Likelihoods with GLIM
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