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-4.7)decomposedPSF_0.2.zip(r-4.6)decomposedPSF_0.2.zip(r-4.5)
decomposedPSF_0.2.tgz(r-4.6-any)decomposedPSF_0.2.tgz(r-4.5-any)
decomposedPSF_0.2.tar.gz(r-4.7-any)decomposedPSF_0.2.tar.gz(r-4.6-any)
decomposedPSF_0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
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 from:aa689c974c. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 146 | ||
| source / vignettes | OK | 181 | ||
| linux-release-x86_64 | OK | 182 | ||
| macos-release-arm64 | OK | 148 | ||
| macos-oldrel-arm64 | OK | 165 | ||
| windows-devel | OK | 86 | ||
| windows-release | OK | 96 | ||
| windows-oldrel | OK | 95 | ||
| wasm-release | OK | 141 |
Exports:eemdarimaeemdpsfeemdpsfarimaemdarimaemdpsfemdpsfarimalpsf
Dependencies:cliclustercolorspacecpp11curldata.tablefarverforecastfracdiffgenericsggplot2gluegtableisobandjsonlitelabelinglatticelifecyclelmtestmagrittrnlmennetPSFquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangRlibeemdS7scalestimeDatetseriesTTRurcavctrsviridisLitewithrxtszoo
