On the goodness-of-fit of generalized linear geostatistical models

Giorgi, Emanuele (2018) On the goodness-of-fit of generalized linear geostatistical models. Spatial Statistics, 28. pp. 79-83. ISSN 2211-6753

[thumbnail of 801.04111]
Preview
PDF (801.04111)
1801.04111.pdf - Accepted Version
Available under License Creative Commons Attribution-NonCommercial-NoDerivs.

Download (296kB)

Abstract

We propose a generalization of Zhang’s coefficient of determination to generalized linear geostatistical models and illustrate its application to river-blindness mapping. The generalized coefficient of determination has a more intuitive interpretation than other measures of predictive performance and allows to assess the individual contribution of each explanatory variable and the random effects to spatial prediction. The developed methodology is also more widely applicable to any generalized linear mixed model.

Item Type:
Journal Article
Journal or Publication Title:
Spatial Statistics
Additional Information:
This is the author’s version of a work that was accepted for publication in Spatial Statistics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Spatial Statistics, 28, 2018 DOI: 10.1016/j.spasta.2018.01.002
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1900/1903
Subjects:
?? coefficient of determinationgeneralized linear geostatistical modelsgoodness-of-fitcomputers in earth sciencesstatistics and probabilitymanagement, monitoring, policy and law ??
ID Code:
123467
Deposited By:
Deposited On:
16 Feb 2018 10:30
Refereed?:
Yes
Published?:
Published
Last Modified:
02 Oct 2024 00:11