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decomposedPSF  

Time Series Prediction with PSF and Decomposition Methods (EMD and EEMD)
View on CRAN: Click here


Download and install decomposedPSF package within the R console
Install from CRAN:
install.packages("decomposedPSF")

Install from Github:
library("remotes")
install_github("cran/decomposedPSF")

Install by package version:
library("remotes")
install_version("decomposedPSF", "0.2")



Attach the package and use:
library("decomposedPSF")
Maintained by
Neeraj Bokde
[Scholar Profile | Author Map]
First Published: 2017-07-09
Latest Update: 2022-05-01
Description:
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.
How to cite:
Neeraj Bokde (2017). decomposedPSF: Time Series Prediction with PSF and Decomposition Methods (EMD and EEMD). R package version 0.2, https://cran.r-project.org/web/packages/decomposedPSF. Accessed 29 Mar. 2025.
Previous versions and publish date:
0.1.3 (2017-07-09 10:26)
Other packages that cited decomposedPSF R package
View decomposedPSF citation profile
Other R packages that decomposedPSF depends, imports, suggests or enhances
Complete documentation for decomposedPSF
Functions, R codes and Examples using the decomposedPSF R package
Some associated functions: eemdarima . eemdpsf . eemdpsfarima . emdarima . emdpsf . emdpsfarima . lpsf . 
Some associated R codes: eemdarima.R . eemdpsf.R . eemdpsfarima.R . emdarima.R . emdpsf.R . emdpsfarima.R . lpsf.R .  Full decomposedPSF package functions and examples
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