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 165 downloads 1 exports 51 dependencies

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

TargetResultDate
Doc / VignettesOKNov 04 2024
R-4.5-linuxOKNov 04 2024

Exports:EMDANNhybrid

Dependencies:clicolorspacecurldotCall64EMDfansifarverfieldsforecastfracdiffgenericsggplot2gluegtableisobandjsonlitelabelinglatticelifecyclelmtestlocfitmagrittrmapsMASSMatrixmgcvmunsellnlmennetpillarpkgconfigquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangscalesspamtibbletimeDatetseriesTTRurcautf8vctrsviridisLitewithrxtszoo

EMDANNhybrid

Rendered fromEMDANNhybrid.Rmdusingknitr::rmarkdownon Nov 04 2024.

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