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.
Version: 0.1.4 Depends: R (≥ 3.5.0) Imports: MBC, WaveletComp, matrixStats, ggplot2 Suggests: stats, tidyr, dplyr, wmtsa, scales, data.table, graphics, testthat (≥ 3.0.0), knitr, rmarkdown, bookdown Published: 2024-10-11 DOI: 10.32614/CRAN.package.WQM Author: Ze Jiang [aut, cre], Fiona Johnson [aut] Maintainer: Ze Jiang <ze.jiang at unsw.edu.au> License: GPL (≥ 3) NeedsCompilation: no Materials: README CRAN checks: WQM results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=WQM to link to this page.
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