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Local Influence for Spatially Correlated Binomial Data: An Application to the Spodoptera frugiperda Infestation in Corn

2017-12-01

Abstract excerpt

Influence diagnostics are valuable tools for understanding the influence of data and/or model assumptions on the results of a statistical analysis. This paper proposes local influence for the analysis of spatially correlated binomial data. We consider a spatial model with a binomial marginal distribution and logit link function. Generalized estimating equations via Fisher’s scoring are used for estimating the para...

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Literature Corpus work
ab830388-26ed-5d20-bd9a-63955937dbd1
DOI
10.1007/s13253-017-0306-5
Open publication

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Local Influence for Spatially Correlated Binomial Data: An Application to the Spodoptera frugiperda Infestation in CornDOI 10.1007/s13253-017-0306-5
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