Package: WaveletGBM
Type: Package
Title: Wavelet Based Gradient Boosting Method
Version: 0.1.0
Authors@R: c(person(" Dr. Ranjit Kumar", "Paul", role = c("aut","cre"), email = "ranjitstat@gmail.com"),
    person("Dr. Md", "Yeasin", role = "aut", email = "yeasin.iasri@gmail.com"))
Author: Dr. Ranjit Kumar Paul [aut, cre],
  Dr. Md Yeasin [aut]
Maintainer: Dr. Ranjit Kumar Paul <ranjitstat@gmail.com>
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>.
License: GPL-3
Encoding: UTF-8
Imports: caret, dplyr, caretForecast, Metrics, tseries, stats,
        wavelets, gbm
RoxygenNote: 7.2.1
NeedsCompilation: no
Packaged: 2023-04-06 07:54:16 UTC; YEASIN
Repository: CRAN
Date/Publication: 2023-04-07 08:20:02 UTC
Built: R 4.5.2; ; 2025-11-08 05:09:53 UTC; windows
