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) <doi:10.1080/13658816.2022.2097684>). The package and its capabilities are described in (Dambon et al. (2021c) <doi:10.48550/arXiv.2106.02364>).

Version:	0.3.4
Depends:	R (≥ 3.5.0)
Imports:	glmnet, lhs, methods, mlr, mlrMBO, optimParallel (≥ 0.8-1), ParamHelpers, pbapply, smoof, spam
Suggests:	DiceKriging, knitr, lattice, latticeExtra, parallel, rmarkdown, sp, spData, testthat (≥ 3.0.0)
Published:	2022-09-17
Author:	Jakob A. Dambon [aut, cre], Fabio Sigrist [ctb], Reinhard Furrer [ctb]
Maintainer:	Jakob A. Dambon <jakob.dambon at math.uzh.ch>
BugReports:	https://github.com/jakobdambon/varycoef/issues
License:	GPL-2
URL:	https://github.com/jakobdambon/varycoef
NeedsCompilation:	no
Citation:	varycoef citation info
In views:	Spatial
CRAN checks:	varycoef results

Documentation:

Reference manual:	varycoef.pdf
Vignettes:	Introduction

Downloads:

Package source:	varycoef_0.3.4.tar.gz
Windows binaries:	r-devel: varycoef_0.3.4.zip, r-release: varycoef_0.3.4.zip, r-oldrel: varycoef_0.3.4.zip
macOS binaries:	r-release (arm64): varycoef_0.3.4.tgz, r-oldrel (arm64): varycoef_0.3.4.tgz, r-release (x86_64): varycoef_0.3.4.tgz, r-oldrel (x86_64): varycoef_0.3.4.tgz
Old sources:	varycoef archive

Linking:

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