Automated multi-path General-to-Specific (GETS) model selection of either an AR-X model with log-ARCH-X errors, or a log-ARCH-X model of the log-variance. The three main functions of the package are arx, getsm and getsv. The first function estimates an AR-X model with log-ARCH-X errors. The second function undertakes GETS model selection of the mean specification of an arx object, whereas the third function undertakes GETS model selection of the log-variance specification of an arx object.

General-to-Specific (GETS) Modelling and Indicator Saturation
Methods
Genaro Sucarrat [aut, cre], Felix Pretis [aut], James Reade [aut]
Automated General-to-Specific (GETS) modelling of the mean and variance of a regression, and indicator saturation methods for detecting and testing for structural breaks in the mean.

Felix Pretis, James Reade, Genaro Sucarrat
Automated multi-path General-to-Specific (GETS) modelling of the mean and variance of a regression, and indicator saturation methods for detecting structural breaks in the mean. The mean can be specified as an autoregressive model with covariates (an 'AR-X' model), and the variance can be specified as a log-variance model with covariates (a 'log-ARCH-X' model). The four main functions of the package are arx, getsm, getsv and isat. The first function, arx, estimates an AR-X model with log-ARCH-X errors. The second function, getsm, undertakes GETS model selection of the mean specification of an arx object. The third function, getsv, undertakes GETS model selection of the log-variance specification of an arx object. The fourth function, isat, undertakes GETS model selection of an indicator saturated mean specification.

Genaro Sucarrat [aut, cre], Felix Pretis [aut], James Reade [aut], Jonas Kurle [ctb], Moritz Schwarz [ctb]
Automated General-to-Specific (GETS) modelling of the mean and variance of a regression, and indicator saturation methods for detecting and testing for structural breaks in the mean, see Pretis, Reade and Sucarrat (2018) <doi:10.18637/jss.v086.i03>.