WaveletArima
Wavelet-ARIMA Model for Time Series Forecasting
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.
- Version0.1.2
- R versionunknown
- LicenseGPL-3
- Needs compilation?No
- Last release07/02/2022
Team
Dr. Ranjit Kumar Paul
Dr. Md Yeasin
Show author detailsRolesAuthorMr. Sandipan Samanta
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- Imports3 packages
- Reverse Imports1 package