Introduction | Installation | Getting Started | Identifying Spatial Autocorrelation | Unsupervised Spatial Filtering in Linear Models | Extension to Generalized Linear Models | References
Package: spfilteR 2.2.0
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.
Authors:
spfilteR_2.2.0.tar.gz
spfilteR_2.2.0.zip(r-4.7-any)spfilteR_2.2.0.zip(r-4.6-any)spfilteR_2.2.0.zip(r-4.5-any)
spfilteR_2.2.0.tgz(r-4.6-any)spfilteR_2.2.0.tgz(r-4.5-any)
spfilteR_2.2.0.tar.gz(r-4.7-any)spfilteR_2.2.0.tar.gz(r-4.6-any)
spfilteR_2.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
spfilteR/json (API)
| # Install 'spfilteR' in R: |
| install.packages('spfilteR', repos = c('https://sjuhl.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/sjuhl/spfilter/issues
Datasets:
- fakedataset - Synthetic Dataset
- W - Synthetic Dataset
Last updated from:1e4262304c. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 190 | ||
| source / vignettes | OK | 149 | ||
| linux-release | OK | 188 | ||
| macos-release | OK | 275 | ||
| macos-oldrel | OK | 238 | ||
| windows-devel | OK | 220 | ||
| windows-release | OK | 224 | ||
| windows-oldrel | OK | 183 | ||
| wasm-release | OK | 72 |
Exports:getEVsglmFilterlmFilterMI.decompMI.evMI.localMI.residMI.sfMI.vecpartialR2vif.evvp
Dependencies:
