Package: EMDANNhybrid 0.2.0

Pankaj Das

EMDANNhybrid: Empirical Mode Decomposition Based Artificial Neural Network Model

Application of empirical mode decomposition based artificial neural network model for nonlinear and non stationary univariate time series forecasting. For method details see (i) Choudhury (2019) <https://www.indianjournals.com/ijor.aspx?target=ijor:ijee3&volume=55&issue=1&article=013>; (ii) Das (2020) <https://www.indianjournals.com/ijor.aspx?target=ijor:ijee3&volume=56&issue=2&article=002>.

Authors:Pankaj Das [aut, cre], Achal Lama [aut], Girish Kumar Jha [aut]

EMDANNhybrid_0.2.0.tar.gz
EMDANNhybrid_0.2.0.tar.gz(r-4.5-noble)EMDANNhybrid_0.2.0.tar.gz(r-4.4-noble)
EMDANNhybrid_0.2.0.tgz(r-4.4-emscripten)EMDANNhybrid_0.2.0.tgz(r-4.3-emscripten)
EMDANNhybrid.pdf |EMDANNhybrid.html✨
EMDANNhybrid/json (API)

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

Peer review:

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

2.00 score 3 scripts 138 downloads 1 exports 51 dependencies

Last updated 1 years agofrom:c9c4e17412. Checks:2 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKJan 03 2025
R-4.5-linuxOKJan 03 2025

Exports:EMDANNhybrid

Dependencies:clicolorspacecurldotCall64EMDfansifarverfieldsforecastfracdiffgenericsggplot2gluegtableisobandjsonlitelabelinglatticelifecyclelmtestlocfitmagrittrmapsMASSMatrixmgcvmunsellnlmennetpillarpkgconfigquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangscalesspamtibbletimeDatetseriesTTRurcautf8vctrsviridisLitewithrxtszoo

EMDANNhybrid

Rendered fromEMDANNhybrid.Rmdusingknitr::rmarkdownon Jan 03 2025.

Last update: 2023-09-14
Started: 2023-09-14