Package: WQM 0.1.4
Ze Jiang
WQM: Wavelet-Based Quantile Mapping for Postprocessing Numerical Weather Predictions
The wavelet-based quantile mapping (WQM) technique is designed to correct biases in spatio-temporal precipitation forecasts across multiple time scales. The WQM method effectively enhances forecast accuracy by generating an ensemble of precipitation forecasts that account for uncertainties in the prediction process. For a comprehensive overview of the methodologies employed in this package, please refer to Jiang, Z., and Johnson, F. (2023) <doi:10.1029/2022EF003350>. The package relies on two packages for continuous wavelet transforms: 'WaveletComp', which can be installed automatically, and 'wmtsa', which is optional and available from the CRAN archive <https://cran.r-project.org/src/contrib/Archive/wmtsa/>. Users need to manually install 'wmtsa' from this archive if they prefer to use 'wmtsa' based decomposition.
Authors:
WQM_0.1.4.tar.gz
WQM_0.1.4.tar.gz(r-4.5-noble)WQM_0.1.4.tar.gz(r-4.4-noble)
WQM_0.1.4.tgz(r-4.4-emscripten)WQM_0.1.4.tgz(r-4.3-emscripten)
WQM.pdf |WQM.html✨
WQM/json (API)
| # Install 'WQM' in R: |
| install.packages('WQM', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 months agofrom:f054c2244c. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 11 2024 |
| R-4.5-linux | OK | Dec 11 2024 |
Exports:bc_cwtfun_cwt_Jfun_icwtfun_ifftprsimRankHist
Dependencies:bootclicolorspaceenergyfansifarverFNNggplot2gluegslgtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmatrixStatsMBCmgcvmunsellnlmepillarpkgconfigR6RColorBrewerRcpprlangscalestibbleutf8vctrsviridisLiteWaveletCompwithr
