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WaveletGBM
View on CRAN: Click
here
Download and install WaveletGBM package within the R console
Install from CRAN:
install.packages("WaveletGBM")
Install from Github:
library("remotes")
install_github("cran/WaveletGBM")
Install by package version:
library("remotes")
install_version("WaveletGBM", "0.1.0")
Attach the package and use:
library("WaveletGBM")
Maintained by
Dr. Ranjit Kumar Paul
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All associated links for this package
First Published: 2023-04-07
Latest Update: 2023-04-07
Description:
Wavelet decomposition method is very useful for modelling noisy time series data. Wavelet decomposition using 'haar' algorithm has been implemented to developed hybrid Wavelet GBM (Gradient Boosting Method) model for time series forecasting using algorithm by Anjoy and Paul (2017) <doi:10.1007/s00521-017-3289-9>.
How to cite:
Dr. Ranjit Kumar Paul (2023). WaveletGBM: Wavelet Based Gradient Boosting Method. R package version 0.1.0, https://cran.r-project.org/web/packages/WaveletGBM. Accessed 06 Oct. 2024.
Previous versions and publish date:
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