varycoef swMATH ID: 38767 Software Authors: Jakob A. Dambon, Fabio Sigrist, Reinhard Furrer Description: R package varycoef: Modeling Spatially Varying Coefficients. Implements a maximum likelihood estimation (MLE) method for estimation and prediction of Gaussian process-based spatially varying coefficient (SVC) models (Dambon et al. (2021a) <doi:10.1016/j.spasta.2020.100470>). Covariance tapering (Furrer et al. (2006) <doi:10.1198/106186006X132178>) can be applied such that the method scales to large data. Further, it implements a joint variable selection of the fixed and random effects (Dambon et al. (2021b) <arXiv:2101.01932>). Homepage: https://cran.r-project.org/web/packages/varycoef/index.html Source Code: https://github.com/cran/varycoef Dependencies: R Keywords: arXiv_stat.CO; arXiv_stat.ME; R; R package; varycoef; spatially varying coefficient; SVC; covariance tapering; dependent data; model-based optimization spatial statistics; maximum likelihood estimation; variable selection Related Software: RandomFields; fpp2; mlrMBO; mlr; ParamHelpers; lhs; glmnet; spData; optimParallel; spam; GRASS GIS; ArcGIS; Pysal; mboost; mgcv; INLA; spBayes; spTDyn; gwrr; spgwr; GWmodel Cited in: 0 Documents Standard Articles 1 Publication describing the Software Year varycoef: An R Package for Gaussian Process-based Spatially Varying Coefficient Models arXiv Jakob A. Dambon, Fabio Sigrist, Reinhard Furrer 2021