varycoef: Modeling Spatially Varying Coefficients

Implements a maximum likelihood estimation (MLE) method for estimation and prediction in spatially varying coefficient (SVC) models (Dambon et al. (2020) <arXiv:2001.08089>). Covariance tapering (Furrer et al. (2006) <doi:10.1198/106186006X132178>) can be applied such that the method scales to large data.

Version: 0.2.11
Depends: spam
Imports: RandomFields, fields, optimParallel (≥ 0.8-1), sp
Suggests: gstat, knitr, microbenchmark, parallel, rmarkdown, R.rsp
Published: 2020-04-14
Author: Jakob A. Dambon ORCID iD [aut, cre], Fabio Sigrist ORCID iD [ctb], Reinhard Furrer ORCID iD [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
CRAN checks: varycoef results

Downloads:

Reference manual: varycoef.pdf
Vignettes: Manual
example
Package source: varycoef_0.2.11.tar.gz
Windows binaries: r-devel: varycoef_0.2.11.zip, r-release: varycoef_0.2.11.zip, r-oldrel: varycoef_0.2.11.zip
macOS binaries: r-release: varycoef_0.2.11.tgz, r-oldrel: varycoef_0.2.11.tgz
Old sources: varycoef archive

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