Wavelet ANN Model
Overview
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>.
Install
Health
- OK13 OK2026-09-08
- ERROR12 OK, 1 ERROR2026-09-07
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
Downloads
Dependencies
Installing WaveletANN adds 30 packages (17 with compiled code, 21 MB of source tarballs). Heaviest: ggplot2 6.0 MB, colorspace 2.0 MB, Rcpp 1.8 MB.
Code & Tests
People & History
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- 0.1.2Latest
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- RR 3.6.0 released · 2019-04-26
- 0.1.02019-03-17
- RR 3.5.0 released · 2018-04-23
Package metadata
- First published
- 2019-03-17
- Total releases
- 2 / 7 yrs
- License
- GPL-3 OSI
- Download size
- 3.1 KB
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("WaveletANN")This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-19, which the citation names so these numbers can be found later. More on citing and the projects behind them.