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Description

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>.
Metadata

Version

0.1.2

License

Unknown

Platforms (75)

    Darwin
    FreeBSD 13
    Genode
    GHCJS
    Linux
    MMIXware
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    none
    OpenBSD
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    Solaris
    WASI
    Windows
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