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Spatial prediction of counts and rates
Author(s) -
Gotway Carol A.,
Wolfinger Russell D.
Publication year - 2003
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.1523
Subject(s) - computer science , strengths and weaknesses , generalized linear model , focus (optics) , count data , econometrics , spatial analysis , statistics , generalized linear mixed model , kriging , linear model , data mining , machine learning , mathematics , philosophy , physics , epistemology , optics , poisson distribution
In this paper we provide both theoretical and empirical comparisons of marginal and conditional methods for analysing spatial count data. We focus on methods for spatial prediction developed from a generalized linear mixed model framework and compare them with the traditional linear (kriging) predictor. Prediction methods are illustrated and compared through a case study based on real data and through a detailed simulation study. The paper emphasizes a better understanding of the strengths and weaknesses of each approach. Published in 2003 by John Wiley & Sons, Ltd.