Package: eemdARIMA 0.1.0

eemdARIMA: EEMD Based Auto Regressive Integrated Moving Average Model

Forecasting time series with different decomposition based ARIMA models. For method details see Yu L, Wang S, Lai KK (2008). <doi:10.1016/j.eneco.2008.05.003>.

Authors:Rajeev Ranjan Kumar [aut, cre], Girish Kumar Jha [aut, ths, ctb], Kapil Choudhary [aut, ctb], Ronit Jaiswal [ctb]

eemdARIMA_0.1.0.tar.gz
eemdARIMA_0.1.0.zip(r-4.5)eemdARIMA_0.1.0.zip(r-4.4)eemdARIMA_0.1.0.zip(r-4.3)
eemdARIMA_0.1.0.tgz(r-4.4-any)eemdARIMA_0.1.0.tgz(r-4.3-any)
eemdARIMA_0.1.0.tar.gz(r-4.5-noble)eemdARIMA_0.1.0.tar.gz(r-4.4-noble)
eemdARIMA_0.1.0.tgz(r-4.4-emscripten)eemdARIMA_0.1.0.tgz(r-4.3-emscripten)
eemdARIMA.pdf |eemdARIMA.html
eemdARIMA/json (API)

# Install 'eemdARIMA' in R:
install.packages('eemdARIMA', repos = c('https://rrk4910.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • Data_Maize - Monthly International Maize Price Data

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 206 downloads 2 exports 46 dependencies

Last updated 3 years agofrom:1d0a31c494. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 23 2024
R-4.5-winOKNov 23 2024
R-4.5-linuxOKNov 23 2024
R-4.4-winOKNov 23 2024
R-4.4-macOKNov 23 2024
R-4.3-winOKNov 23 2024
R-4.3-macOKNov 23 2024

Exports:EEMDARIMAemdARIMA

Dependencies:clicolorspacecurlfansifarverforecastfracdiffgenericsggplot2gluegtableisobandjsonlitelabelinglatticelifecyclelmtestmagrittrMASSMatrixmgcvmunsellnlmennetpillarpkgconfigquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangRlibeemdscalestibbletimeDatetseriesTTRurcautf8vctrsviridisLitewithrxtszoo