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.
Package details |
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Author | James Balamuta [aut, cph], Stephane Guerrier [ctb, cre, cph], Roberto Molinari [ctb, cph], Wenchao Yang [ctb] |
Maintainer | Stephane Guerrier <stephane@illinois.edu> |
License | CC BY-NC-SA 4.0 |
Version | 2.0.0 |
URL | https://github.com/SMAC-Group/gmwm |
Package repository | View on CRAN |
Installation |
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