An open-source wavelet tool for improving prediction accuracy for natural system models.
The wavelet-based variance transformation method is used for system modelling and prediction. It refines predictor spectral representation using Wavelet Theory, which leads to improved model specifications and prediction accuracy.
Dependencies: waveslim, stats, tidyr, ggplot2, spSuggest: zoo, readr, cowplot, SPEI, FNN, NPRED, synthesis, fitdistrplus
You can install the package via devtools from GitHub with:
devtools::install_github("zejiang-unsw/WASP", dependencies = TRUE)
or via CRAN with:
install.packages("WASP")
Jiang, Z., Sharma, A., & Johnson, F. (2021). Variable transformations in the spectral domain – Implications for hydrologic forecasting. Journal of Hydrology, 603, 126816. doi
Jiang, Z., Rashid, M. M., Johnson, F., & Sharma, A. (2020). A wavelet-based tool to modulate variance in predictors: an application to predicting drought anomalies. Environmental Modelling & Software, 135, 104907. doi
Jiang, Z., Sharma, A., & Johnson, F. (2020). Refining Predictor Spectral Representation Using Wavelet Theory for Improved Natural System Modeling. Water Resources Research, 56(3), e2019WR026962. doi
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