Package: sta 0.1.7
Inder Tecuapetla-Gomez
sta: Seasonal Trend Analysis for Time Series Imagery in R
Efficiently estimate shape parameters of periodic time series imagery with which a statistical seasonal trend analysis (STA) is subsequently performed. STA output can be exported in conventional raster formats. Methods to visualize STA output are also implemented as well as the calculation of additional basic statistics. STA is based on (R. Eastman, F. Sangermano, B. Ghimire, H. Zhu, H. Chen, N. Neeti, Y. Cai, E. Machado and S. Crema, 2009) <doi:10.1080/01431160902755338>.
Authors:
sta_0.1.7.tar.gz
sta_0.1.7.tar.gz(r-4.5-noble)sta_0.1.7.tar.gz(r-4.4-noble)
sta_0.1.7.tgz(r-4.4-emscripten)sta_0.1.7.tgz(r-4.3-emscripten)
sta.pdf |sta.html✨
sta/json (API)
| # Install 'sta' in R: |
| install.packages('sta', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- marismas - 10-day Composite NDMI Time Series
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:790c9b733b. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 11 2024 |
| R-4.5-linux | OK | Dec 11 2024 |
Dependencies:base64encbitbrewbslibcachemclassclassIntclicodetoolscolorspacecpp11crosstalkDBIDEoptimRdigestdoParallele1071evaluateextraDistrfarverfastmapfffontawesomeforeachfsgeojsonsfgeometriesgeoTSgluehighrhtmltoolshtmlwidgetshttpuviteratorsjquerylibjsonifyjsonliteKernSmoothknitrlabelinglaterlatticelazyevalleafemleafletleaflet.providersleafpoplifecyclemagrittrmapviewMASSmemoisemimemunsellplyrpngpromisesproxyR6rapidjsonrrappdirsrasterRColorBrewerRcpprlangrmarkdownrobustbases2sasssatellitescalesservrsfsfheadersspsvglitesystemfontsterratinytextrendunitsuuidviridisLitewkxfunyaml
