CRAN/E | WaveletArima

WaveletArima

Wavelet-ARIMA Model for Time Series Forecasting

Installation

About

Noise in the time-series data significantly affects the accuracy of the ARIMA model. Wavelet transformation decomposes the time series data into subcomponents to reduce the noise and help to improve the model performance. The wavelet-ARIMA model can achieve higher prediction accuracy than the traditional ARIMA model. This package provides Wavelet-ARIMA model for time series forecasting based on the algorithm by Aminghafari and Poggi (2012) and Paul and Anjoy (2018) doi:10.1142/S0219691307002002 doi:10.1007/s00704-017-2271-x.

Key Metrics

Version 0.1.2
Published 2022-07-02 656 days ago
Needs compilation? no
License GPL-3
CRAN checks WaveletArima results

Downloads

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Maintainer

Maintainer

Dr. Ranjit Kumar Paul

ranjitstat@gmail.com

Authors

Dr. Ranjit Kumar Paul

aut / cre

Mr. Sandipan Samanta

aut

Dr. 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

Old Sources

WaveletArima archive

Imports

stats
wavelets
fracdiff
forecast