Package: decomposedPSF 0.2
decomposedPSF: Time Series Prediction with PSF and Decomposition Methods (EMD and EEMD)
Predict future values with hybrid combinations of Pattern Sequence based Forecasting (PSF), Autoregressive Integrated Moving Average (ARIMA), Empirical Mode Decomposition (EMD) and Ensemble Empirical Mode Decomposition (EEMD) methods based hybrid methods.
Authors:
decomposedPSF_0.2.tar.gz
decomposedPSF_0.2.zip(r-4.5)decomposedPSF_0.2.zip(r-4.4)decomposedPSF_0.2.zip(r-4.3)
decomposedPSF_0.2.tgz(r-4.4-any)decomposedPSF_0.2.tgz(r-4.3-any)
decomposedPSF_0.2.tar.gz(r-4.5-noble)decomposedPSF_0.2.tar.gz(r-4.4-noble)
decomposedPSF_0.2.tgz(r-4.4-emscripten)decomposedPSF_0.2.tgz(r-4.3-emscripten)
decomposedPSF.pdf |decomposedPSF.html✨
decomposedPSF/json (API)
| # Install 'decomposedPSF' in R: |
| install.packages('decomposedPSF', repos = c('https://neerajdhanraj.r-universe.dev', 'https://cloud.r-project.org')) |
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:aa689c974c. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 01 2024 |
| R-4.5-win | OK | Nov 01 2024 |
| R-4.5-linux | OK | Nov 01 2024 |
| R-4.4-win | OK | Nov 01 2024 |
| R-4.4-mac | OK | Nov 01 2024 |
| R-4.3-win | OK | Nov 01 2024 |
| R-4.3-mac | OK | Nov 01 2024 |
Exports:eemdarimaeemdpsfeemdpsfarimaemdarimaemdpsfemdpsfarimalpsf
Dependencies:cliclustercolorspacecurldata.tablefansifarverforecastfracdiffgenericsggplot2gluegtableisobandjsonlitelabelinglatticelifecyclelmtestmagrittrMASSMatrixmgcvmunsellnlmennetpillarpkgconfigPSFquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangRlibeemdscalestibbletimeDatetseriesTTRurcautf8vctrsviridisLitewithrxtszoo
