Generalized Method of Wavelet Moments (GMWM) is an estimation technique for the parameters of time series models. It uses the wavelet variance in a moment matching approach that makes it particularly suitable for the estimation of certain state-space models. Furthermore, there exists a robust implementation of GMWM, which allows the robust estimation of some state-space models and ARIMA models. Lastly, the package provides the ability to quickly generate time series data, perform different wavelet decompositions, and visualizations.
|Author||James Balamuta [aut, cph], Stephane Guerrier [ctb, cre, cph], Roberto Molinari [ctb, cph], Wenchao Yang [ctb]|
|Maintainer||Stephane Guerrier <[email protected]>|
|License||CC BY-NC-SA 4.0|
|Package repository||View on CRAN|
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