Package: widals 0.6.1
widals: Weighting by Inverse Distance with Adaptive Least Squares
Computationally easy modeling, interpolation, forecasting of massive temporal-spacial data.
Authors:
widals_0.6.1.tar.gz
widals_0.6.1.zip(r-4.5)widals_0.6.1.zip(r-4.4)widals_0.6.1.zip(r-4.3)
widals_0.6.1.tgz(r-4.4-x86_64)widals_0.6.1.tgz(r-4.4-arm64)widals_0.6.1.tgz(r-4.3-x86_64)widals_0.6.1.tgz(r-4.3-arm64)
widals_0.6.1.tar.gz(r-4.5-noble)widals_0.6.1.tar.gz(r-4.4-noble)
widals_0.6.1.tgz(r-4.4-emscripten)widals_0.6.1.tgz(r-4.3-emscripten)
widals.pdf |widals.html✨
widals/json (API)
| # Install 'widals' in R: |
| install.packages('widals', repos = c('https://davezes.r-universe.dev', 'https://cloud.r-project.org')) |
- O3 - California Ozone
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 5 years agofrom:c431b52c04. Checks:OK: 7 NOTE: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 08 2024 |
| R-4.5-win-x86_64 | NOTE | Oct 08 2024 |
| R-4.5-linux-x86_64 | NOTE | Oct 08 2024 |
| R-4.4-win-x86_64 | OK | Oct 08 2024 |
| R-4.4-mac-x86_64 | OK | Oct 08 2024 |
| R-4.4-mac-aarch64 | OK | Oct 08 2024 |
| R-4.3-win-x86_64 | OK | Oct 08 2024 |
| R-4.3-mac-x86_64 | OK | Oct 08 2024 |
| R-4.3-mac-aarch64 | OK | Oct 08 2024 |
Exports:applystnd.Hsapplystnd.Hst.lscreate.rm.ndx.lscrispifydistancedlog.normfun.load.hals.afun.load.hals.fillfun.load.widals.afun.load.widals.fillfuse.Hst.lsH.als.bH.Earth.solarHals.fastcv.snowHals.sesHals.snowHst.sumupload.Hst.ls.2Zsload.Hst.ls.ZMSS.snowrm.cols.Hst.lsstnd.Hsstnd.Hst.lsstnd.Htsubsetsites.Hst.lsunif.mhunload.Hst.lswidals.predictwidals.snowZ.clean.up
