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spfilteR: Semiparametric Spatial Filtering with Eigenvectors in (Generalized) Linear Models

Tools to decompose (transformed) spatial connectivity matrices and perform supervised or unsupervised semiparametric spatial filtering in a regression framework. The package supports unsupervised spatial filtering in standard linear as well as some generalized linear regression models.

Version: 1.1.5
Depends: R (≥ 3.5.0)
Imports: stats
Suggests: testthat, knitr, rmarkdown
Published: 2022-08-22
DOI: 10.32614/CRAN.package.spfilteR
Author: Sebastian Juhl ORCID iD [aut, cre]
Maintainer: Sebastian Juhl <sebastian.juhl at t-online.de>
BugReports: https://github.com/sjuhl/spfilteR/issues
License: GPL-3
URL: https://github.com/sjuhl/spfilteR
NeedsCompilation: no
Citation: spfilteR citation info
Materials: README NEWS
CRAN checks: spfilteR results

Documentation:

Reference manual: spfilteR.pdf
Vignettes: spfilteR: Semiparametric Spatial Filtering with Eigenvectors in (Generalized) Linear Models

Downloads:

Package source: spfilteR_1.1.5.tar.gz
Windows binaries: r-devel: spfilteR_1.1.5.zip, r-release: spfilteR_1.1.5.zip, r-oldrel: spfilteR_1.1.5.zip
macOS binaries: r-release (arm64): spfilteR_1.1.5.tgz, r-oldrel (arm64): spfilteR_1.1.5.tgz, r-release (x86_64): spfilteR_1.1.5.tgz, r-oldrel (x86_64): spfilteR_1.1.5.tgz
Old sources: spfilteR archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.