spmodel Workshop - Spatial Statistics 2023: Climate and the Environment
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The spmodel R package can be used to fit, summarize, and predict for a variety of spatial statistical models for both point-referenced and areal spatial data. What distinguishes spmodel from many other R packages for modelling spatial data is (1) a syntactic structure similar to the syntactic structure of base R functions lm() and glm() that makes spmodel relatively easy to learn, (2) the breadth of options that give the user a high amount of control over the model being fit, and (3) compatibility with other modern R packages like broom and sf. By the end of this workshop, participants can expect to be able to use spmodel to fit spatial linear models for point-referenced and areal (lattice) data, make predictions for unobserved spatial locations, fit anisotropic models for point-referenced data, fit spatial models with additional non-spatial random effects, fit generalized linear models for spatial data, and use big data methods to analyze large spatial data sets.