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stat.ME2023
Indexing and Partitioning the Spatial Linear Model for Large Data Sets
Jay M. Ver Hoef, Michael Dumelle, Matt Higham +2
We consider four main goals when fitting spatial linear models: 1) estimating covariance parameters, 2) estimating fixed effects, 3) kriging (making point predictions), and 4) bloc…
stat.ME2023
Marginal Inference for Hierarchical Generalized Linear Mixed Models with Patterned Covariance Matrices Using the Laplace Approximation
Jay M. Ver Hoef, Eryn Blagg, Michael Dumelle +3
Using a hierarchical construction, we develop methods for a wide and flexible class of models by taking a fully parametric approach to generalized linear mixed models with complex…