swMATH ID: 21249
Software Authors: James Balamuta, Roberto Molinari, Stéphane Guerrier, Wenchao Yang
Description: The gmwm R package: a comprehensive tool for time series analysis from state-space models to robustness. 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.
Homepage: https://github.com/SMAC-Group/gmwm
Source Code:  https://github.com/SMAC-Group/gmwm
Dependencies: R
Keywords: Computation; arXiv_stat.CO; arXiv_publication; R package; Wavelet variance; Latent models; Structural models; Computational efficiency; Large data
Related Software: R; RcppArmadillo; Rcpp
Cited in: 0 Publications