Package: VMDML 0.1.1

Pankaj Das

VMDML: Variational Mode Decomposition Based Machine Learning Models

Application of Variational Mode Decomposition based different Machine Learning models for univariate time series forecasting. For method details see (i) K. Dragomiretskiy and D. Zosso (2014) <doi:10.1109/TSP.2013.2288675>; (ii) Pankaj Das (2020) <http://krishi.icar.gov.in/jspui/handle/123456789/44138>.

Authors:Pankaj Das [aut, cre], Girish Kumar Jha [aut], Tauqueer Ahmad [aut], Achal Lama [aut], Lampros Mouselimis [cph]

# Install 'VMDML' in R:

install.packages('VMDML', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

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

Last updated from:ee3675d74f. Checks:4 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	151
source / vignettes	OK	185
linux-release-x86_64	OK	132
wasm-release	OK	160

Last update: 2023-08-27
Started: 2023-08-27

Help page	Topics
Variational Mode Decomposition Based Autoregressive Moving Average Model	VMDARIMA
Variational Mode Decomposition Based Extreme Learning Machine Model	VMDELM
Variational Mode Decomposition Based Random Forest Model	VMDRF
Variational Mode Decomposition Based Support Vector Regression Model	VMDSVR
Variational Mode Decomposition Based Time Delay Neural Network Model	VMDTDNN