The gmwm R package: a comprehensive tool for time series analysis from state-space models to robustness

James Balamuta; Roberto Molinari; Stéphane Guerrier; Wenchao Yang

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arXiv · 1607.04543

The gmwm R package: a comprehensive tool for time series analysis from state-space models to robustness

James Balamuta·Roberto Molinari·Stéphane Guerrier·Wenchao Yang

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Abstract

The gmwm R package for inference on time series models is mainly based on the quantity called wavelet variance which is derived from a wavelet decomposition of a time series. This quantity provides a means to summarize and graphically represent the features of time series in order to identify possible models. Moreover, it is used as a moment condition for model estimation through the generalized method of wavelet moments. Based on the latter method, this package not only provides an alternative method to estimate classical ARMA models but also delivers a general framework for the robust estimation of many time series models as well as a quick and efficient estimation of many linear state-space models.

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James Balamuta, Roberto Molinari, Stéphane Guerrier, Wenchao Yang. 2016-07-15. The gmwm R package: a comprehensive tool for time series analysis from state-space models to robustness. https://arxiv.org/abs/1607.04543

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