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:
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')) |
- Data_Maize - Monthly International Maize Price Data
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:1d0a31c494. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 23 2024 |
R-4.5-win | OK | Nov 23 2024 |
R-4.5-linux | OK | Nov 23 2024 |
R-4.4-win | OK | Nov 23 2024 |
R-4.4-mac | OK | Nov 23 2024 |
R-4.3-win | OK | Nov 23 2024 |
R-4.3-mac | OK | Nov 23 2024 |
Dependencies:clicolorspacecurlfansifarverforecastfracdiffgenericsggplot2gluegtableisobandjsonlitelabelinglatticelifecyclelmtestmagrittrMASSMatrixmgcvmunsellnlmennetpillarpkgconfigquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangRlibeemdscalestibbletimeDatetseriesTTRurcautf8vctrsviridisLitewithrxtszoo
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Monthly International Maize Price Data | Data_Maize |
Ensemble Empirical Mode Decomposition Based ARIMA Model | EEMDARIMA |
Empirical Mode Decomposition Based ARIMA Model | emdARIMA |