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-4.7)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✨
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'))

On CRAN:

Conda:

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

2.08 score 12 scripts 211 downloads 7 exports 42 dependencies

Last updated from:aa689c974c. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK146
source / vignettesOK181
linux-release-x86_64OK182
macos-release-arm64OK148
macos-oldrel-arm64OK165
windows-develOK86
windows-releaseOK96
windows-oldrelOK95
wasm-releaseOK141

Exports:eemdarimaeemdpsfeemdpsfarimaemdarimaemdpsfemdpsfarimalpsf

Dependencies:cliclustercolorspacecpp11curldata.tablefarverforecastfracdiffgenericsggplot2gluegtableisobandjsonlitelabelinglatticelifecyclelmtestmagrittrnlmennetPSFquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangRlibeemdS7scalestimeDatetseriesTTRurcavctrsviridisLitewithrxtszoo

decomposedPSF-vignette

Neeraj Bokde

Rendered fromdecomposedPSF-vignette.Rmdusingknitr::rmarkdownon May 25 2026.

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