CF-GLMM extends the coarse-to-fine spatial modeling framework to GLMMs for count data, delivering scalable prediction, multiscale feature extraction, and resolution of degeneracy problems in conventional spatial GLMMs.
The study periods include an early period (January–May 2020) and a late period (July–December 2021)
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Coarse-to-fine spatial GLMM for scalable prediction and multiscale analysis
CF-GLMM extends the coarse-to-fine spatial modeling framework to GLMMs for count data, delivering scalable prediction, multiscale feature extraction, and resolution of degeneracy problems in conventional spatial GLMMs.