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-4.5-any)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'))

On CRAN:

Conda:

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

1.00 score 2 scripts 136 downloads 2 exports 47 dependencies

Last updated 3 years agofrom:10bcbe6ae4. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKApr 01 2025
R-4.5-winOKApr 01 2025
R-4.5-macOKApr 01 2025
R-4.5-linuxOKApr 01 2025
R-4.4-winOKApr 01 2025
R-4.4-macOKApr 01 2025
R-4.4-linuxOKApr 01 2025
R-4.3-winOKApr 01 2025
R-4.3-macOKApr 01 2025

Exports:WaveletFittingWaveletFittingann

Dependencies:clicolorspacecurlfansifarverforecastfracdiffgenericsggplot2gluegtableisobandjsonlitelabelinglatticelifecyclelmtestmagrittrMASSMatrixMetricsmgcvmunsellnlmennetpillarpkgconfigquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangscalestibbletimeDatetseriesTTRurcautf8vctrsviridisLitewaveletswithrxtszoo