Package: epicasting 0.1.0

Tanujit Chakraborty

epicasting: Ewnet: An Ensemble Wavelet Neural Network for Forecasting and Epicasting

Method and tool for generating time series forecasts using an ensemble wavelet-based auto-regressive neural network architecture. This method provides additional support of exogenous variables and also generates confidence interval. This package provides EWNet model for time series forecasting based on the algorithm by Panja, et al. (2022) and Panja, et al. (2023) <arxiv:2206.10696> <doi:10.1016/j.chaos.2023.113124>.

Authors:Madhurima Panja [aut], Tanujit Chakraborty [aut, cre, cph]

epicasting_0.1.0.tar.gz
epicasting_0.1.0.zip(r-4.5)epicasting_0.1.0.zip(r-4.4)epicasting_0.1.0.zip(r-4.3)
epicasting_0.1.0.tgz(r-4.4-any)epicasting_0.1.0.tgz(r-4.3-any)
epicasting_0.1.0.tar.gz(r-4.5-noble)epicasting_0.1.0.tar.gz(r-4.4-noble)
epicasting_0.1.0.tgz(r-4.4-emscripten)epicasting_0.1.0.tgz(r-4.3-emscripten)
epicasting.pdf |epicasting.html✨
epicasting/json (API)

# Install 'epicasting' in R:
install.packages('epicasting', repos = c('https://epiverse-connect.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.

1.00 score 208 downloads 1 exports 47 dependencies

Last updated 2 years agofrom:65900cc614. Checks:OK: 7. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 19 2024
R-4.5-winOKNov 19 2024
R-4.5-linuxOKNov 19 2024
R-4.4-winOKNov 19 2024
R-4.4-macOKNov 19 2024
R-4.3-winOKNov 19 2024
R-4.3-macOKNov 19 2024

Exports:ewnet

Dependencies:clicolorspacecurlfansifarverforecastfracdiffgenericsggplot2gluegtableisobandjsonlitelabelinglatticelifecyclelmtestmagrittrMASSMatrixMetricsmgcvmunsellnlmennetpillarpkgconfigquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangscalestibbletimeDatetseriesTTRurcautf8vctrsviridisLitewaveletswithrxtszoo