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.
Currently, mgmwm cannot handle single data series. This pull request address this by skipping mean computation before estimating the model parameters. Note that the wavelet coefficients have to be encapsluated in a list for a single data series: mgmwm(model, list(wv)). This fix is a workaround for #226. It enables mgmwm to process single data series and "replaces" gmwm.
Currently,
mgmwmcannot handle single data series. This pull request address this by skipping mean computation before estimating the model parameters. Note that the wavelet coefficients have to be encapsluated in a list for a single data series:mgmwm(model, list(wv)). This fix is a workaround for #226. It enablesmgmwmto process single data series and "replaces"gmwm.Example: