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:Neeraj Bokde

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-4.5-any)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'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.56 score 1 packages 12 scripts 211 downloads 7 exports 49 dependencies

Last updated 3 years agofrom:aa689c974c. Checks:8 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 25 2025
R-4.5-winOKFeb 25 2025
R-4.5-macOKFeb 25 2025
R-4.5-linuxOKFeb 25 2025
R-4.4-winOKFeb 25 2025
R-4.4-macOKFeb 25 2025
R-4.3-winOKFeb 25 2025
R-4.3-macOKFeb 25 2025

Exports:eemdarimaeemdpsfeemdpsfarimaemdarimaemdpsfemdpsfarimalpsf

Dependencies:cliclustercolorspacecurldata.tablefansifarverforecastfracdiffgenericsggplot2gluegtableisobandjsonlitelabelinglatticelifecyclelmtestmagrittrMASSMatrixmgcvmunsellnlmennetpillarpkgconfigPSFquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangRlibeemdscalestibbletimeDatetseriesTTRurcautf8vctrsviridisLitewithrxtszoo

decomposedPSF-vignette

Neeraj Bokde

Rendered fromdecomposedPSF-vignette.Rmdusingknitr::rmarkdownon Feb 25 2025.

Last update: 2022-05-01
Started: 2017-07-09