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WaveletSVR
View on CRAN: Click
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Download and install WaveletSVR package within the R console
Install from CRAN:
install.packages("WaveletSVR")
Install from Github:
library("remotes")
install_github("cran/WaveletSVR")
Install by package version:
library("remotes")
install_version("WaveletSVR", "0.1.0")
Attach the package and use:
library("WaveletSVR")
Maintained by
Ranjit Kumar Paul
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-01-06
Latest Update: 2022-01-06
Description:
The main aim of this package is to combine the advantage of wavelet and support vector machine models for time series forecasting. This package also gives the accuracy measurements in terms of RMSE and MAPE. This package fits the hybrid Wavelet SVR model for time series forecasting The main aim of this package is to combine the advantage of wavelet and Support Vector Regression (SVR) models for time series forecasting. This package also gives the accuracy measurements in terms of Root Mean Square Error (RMSE) and Mean Absolute Prediction Error (MAPE). This package is based on the algorithm of Raimundo and Okamoto (2018) <doi:10.1109/INFOCT.2018.8356851>.
How to cite:
Ranjit Kumar Paul (2022). WaveletSVR: Wavelet-SVR Hybrid Model for Time Series Forecasting. R package version 0.1.0, https://cran.r-project.org/web/packages/WaveletSVR
Previous versions and publish date:
No previous versions
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Other R packages that WaveletSVR depends,
imports, suggests or enhances
Functions, R codes and Examples using
the WaveletSVR R package
Some associated functions: WaveletFitting . WaveletFittingsvr .
Some associated R codes: WaveletSVR.R . Full WaveletSVR package functions and examples
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