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:
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')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:10bcbe6ae4. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 02 2024 |
| R-4.5-win | OK | Nov 02 2024 |
| R-4.5-linux | OK | Nov 02 2024 |
| R-4.4-win | OK | Nov 02 2024 |
| R-4.4-mac | OK | Nov 02 2024 |
| R-4.3-win | OK | Nov 02 2024 |
| R-4.3-mac | OK | Nov 02 2024 |
Exports:WaveletFittingWaveletFittingann
Dependencies:clicolorspacecurlfansifarverforecastfracdiffgenericsggplot2gluegtableisobandjsonlitelabelinglatticelifecyclelmtestmagrittrMASSMatrixMetricsmgcvmunsellnlmennetpillarpkgconfigquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangscalestibbletimeDatetseriesTTRurcautf8vctrsviridisLitewaveletswithrxtszoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Wavelet Transform Using Maximal Overlap Discrete Wavelet Transform (MODWT) Algorithm | WaveletFitting |
| Wavelet-ANN Hybrid Model for Forecasting | WaveletFittingann |
