Package: SpatPCA 1.3.8
Wen-Ting Wang
SpatPCA: Regularized Principal Component Analysis for Spatial Data
Provide regularized principal component analysis incorporating smoothness, sparseness and orthogonality of eigen-functions by using the alternating direction method of multipliers algorithm (Wang and Huang, 2017, <doi:10.1080/10618600.2016.1157483>). The method can be applied to either regularly or irregularly spaced data, including 1D, 2D, and 3D.
Authors:
SpatPCA_1.3.8.tar.gz
SpatPCA_1.3.8.tar.gz(r-4.7-arm64)SpatPCA_1.3.8.tar.gz(r-4.7-x86_64)SpatPCA_1.3.8.tar.gz(r-4.6-arm64)SpatPCA_1.3.8.tar.gz(r-4.6-x86_64)
SpatPCA_1.3.8.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
SpatPCA/json (API)
NEWS
| # Install 'SpatPCA' in R: |
| install.packages('SpatPCA', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/egpivo/spatpca/issues
Pkgdown/docs site:https://egpivo.github.io
Last updated from:1aa808defb. Checks:6 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 161 | ||
| linux-devel-x86_64 | OK | 168 | ||
| source / vignettes | OK | 242 | ||
| linux-release-arm64 | OK | 164 | ||
| linux-release-x86_64 | OK | 160 | ||
| wasm-release | OK | 173 |
Exports:checkInputDatacheckNewLocationsForSpatpcaObjectdetrendeigenFunctionfetchUpperBoundNumberEigenfunctionsplot.spatpcapredictpredictEigenfunctionscaleLocationsetCoressetGammasetL2setNumberEigenfunctionssetTau1setTau2spatialPredictionspatpcaspatpcaCVspatpcaCVWithSelectedKthinPlateSplineMatrix
Dependencies:clicpp11farverggplot2gluegtableisobandlabelinglifecycleR6RColorBrewerRcppRcppArmadillorlangS7scalesvctrsviridisLitewithr
Capture the Dominant Spatial Pattern with One-Dimensional Locations
Rendered fromdemo-one-dim-location.Rmdusingknitr::rmarkdownon May 26 2026.Last update: 2025-09-28
Started: 2021-01-31
Capture the Dominant Spatial Pattern with Two-Dimensional Locations
Rendered fromdemo-two-dim-location.Rmdusingknitr::rmarkdownon May 26 2026.Last update: 2025-09-28
Started: 2021-01-31
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Regularized Principal Component Analysis for Spatial Data | SpatPCA-package |
| Display the cross-validation results | plot.spatpca |
| Spatial predictions on new locations | predict |
| Spatial dominant patterns on new locations | predictEigenfunction |
| Regularized PCA for spatial data | spatpca |
| Thin-plane spline matrix | thinPlateSplineMatrix |
