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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