CRAN/E | WaveletRF

WaveletRF

Wavelet-RF Hybrid Model for Time Series Forecasting

Installation

About

The Wavelet Decomposition followed by Random Forest Regression (RF) models have been applied for time series forecasting. The maximum overlap discrete wavelet transform (MODWT) algorithm was chosen as it works for any length of the series. The series is first divided into training and testing sets. In each of the wavelet decomposed series, the supervised machine learning approach namely random forest was employed to train the model. This package also provides accuracy metrics in the form of Root Mean Square Error (RMSE) and Mean Absolute Prediction Error (MAPE). This package is based on the algorithm of Ding et al. (2021) doi:10.1007/s11356-020-12298-3.

Key Metrics

Version 0.1.0
Published 2022-02-22 787 days ago
Needs compilation? no
License GPL-3
CRAN checks WaveletRF results

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Maintainer

Maintainer

Ranjit Kumar Paul

ranjitstat@gmail.com

Authors

Ranjit Kumar Paul

aut / cre

Md Yeasin

aut

Material

Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Imports

stats
wavelets
fracdiff
forecast
randomForest
tsutils