/WASP

WAvelet System Prediction [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.]

Primary LanguageR

WASP

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.

Requirements

Dependencies:
  waveslim, stats, tidyr, ggplot2, sp

Suggest:
    zoo, readr,
    cowplot, SPEI, FNN, 
    NPRED, synthesis, fitdistrplus

Installation

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")

Citation

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