Package: WaveletANN 0.1.2

WaveletANN: Wavelet ANN Model

The wavelet and ANN technique have been combined to reduce the effect of data noise. This wavelet-ANN conjunction model is able to forecast time series data with better accuracy than the traditional time series model. This package fits hybrid Wavelet ANN model for time series forecasting using algorithm by Anjoy and Paul (2017) <doi:10.1007/s00521-017-3289-9>.

Authors:Dr. Ranjit Kumar Paul [aut, cre], Dr. Md Yeasin [aut]

WaveletANN_0.1.2.tar.gz
WaveletANN_0.1.2.zip(r-4.5)WaveletANN_0.1.2.zip(r-4.4)WaveletANN_0.1.2.zip(r-4.3)
WaveletANN_0.1.2.tgz(r-4.4-any)WaveletANN_0.1.2.tgz(r-4.3-any)
WaveletANN_0.1.2.tar.gz(r-4.5-noble)WaveletANN_0.1.2.tar.gz(r-4.4-noble)
WaveletANN_0.1.2.tgz(r-4.4-emscripten)WaveletANN_0.1.2.tgz(r-4.3-emscripten)
WaveletANN.pdf |WaveletANN.html
WaveletANN/json (API)

# Install 'WaveletANN' in R:
install.packages('WaveletANN', repos = c('https://ranjitstat.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2 exports 0.00 score 47 dependencies 2 scripts 215 downloads

Last updated 2 years agofrom:10bcbe6ae4. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 03 2024
R-4.5-winOKSep 03 2024
R-4.5-linuxOKSep 03 2024
R-4.4-winOKSep 03 2024
R-4.4-macOKSep 03 2024
R-4.3-winOKSep 03 2024
R-4.3-macOKSep 03 2024

Exports:WaveletFittingWaveletFittingann

Dependencies:clicolorspacecurlfansifarverforecastfracdiffgenericsggplot2gluegtableisobandjsonlitelabelinglatticelifecyclelmtestmagrittrMASSMatrixMetricsmgcvmunsellnlmennetpillarpkgconfigquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangscalestibbletimeDatetseriesTTRurcautf8vctrsviridisLitewaveletswithrxtszoo