Package: SpatPCA 1.3.5

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:Wen-Ting Wang [aut, cre], Hsin-Cheng Huang [aut]

SpatPCA_1.3.5.tar.gz
SpatPCA_1.3.5.tar.gz(r-4.5-noble)SpatPCA_1.3.5.tar.gz(r-4.4-noble)
SpatPCA_1.3.5.tgz(r-4.4-emscripten)SpatPCA_1.3.5.tgz(r-4.3-emscripten)
SpatPCA.pdf |SpatPCA.html
SpatPCA/json (API)
NEWS

# Install 'SpatPCA' in R:
install.packages('SpatPCA', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/egpivo/spatpca/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

openblascppopenmp

3.23 score 17 scripts 250 downloads 20 exports 31 dependencies

Last updated 1 years agofrom:c1d1d356f4. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKDec 07 2024
R-4.5-linux-x86_64OKDec 07 2024

Exports:checkInputDatacheckNewLocationsForSpatpcaObjectdetrendeigenFunctionfetchUpperBoundNumberEigenfunctionsplot.spatpcapredictpredictEigenfunctionscaleLocationsetCoressetGammasetL2setNumberEigenfunctionssetTau1setTau2spatialPredictionspatpcaspatpcaCVspatpcaCVWithSelectedKthinPlateSplineMatrix

Dependencies:clicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerRcppRcppArmadilloRcppParallelrlangscalestibbleutf8vctrsviridisLitewithr

Capture the Dominant Spatial Pattern with One-Dimensional Locations

Rendered fromdemo-one-dim-location.Rmdusingknitr::rmarkdownon Dec 07 2024.

Last update: 2023-11-13
Started: 2021-01-31

Capture the Dominant Spatial Pattern with Two-Dimensional Locations

Rendered fromdemo-two-dim-location.Rmdusingknitr::rmarkdownon Dec 07 2024.

Last update: 2023-11-13
Started: 2021-01-31