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