spmodel: Spatial statistical modeling and prediction in R
Michael Dumelle, Matt Higham, Jay M. Ver Hoef
Abstract
package used to fit, summarize, and predict for a variety spatial statistical models applied to point-referenced or areal (lattice) data. Parameters are estimated using various methods, including likelihood-based optimization and weighted least squares based on variograms. Additional modeling features include anisotropy, non-spatial random effects, partition factors, big data approaches, and more. Model-fit statistics are used to summarize, visualize, and compare models. Predictions at unobserved locations are readily obtainable.
Topics & Concepts
Computer scienceSpatial analysisStatistical modelStatisticsData miningAlgorithmMathematicsArtificial intelligenceSoil Geostatistics and MappingSpatial and Panel Data AnalysisStatistical Methods and Bayesian Inference