This paper provides an overview of the R package gets, which contains facilities for General-to-Specic (GETS) modelling of the mean and variance of a regression, and Indicator Saturation (IS) methods for the detection and modelling of structural breaks and outliers. The mean can be specied as an autoregressive model with covariates (an `AR-X' model), and the variance can be specied as an autoregressive log-variance model with covariates (a `log-ARCH-X' model). The covariates in the two specications need not be the same, and the classical regression model is obtained as a special case when there is no dynamics, and when there are no covariates in the variance equation. The four main functions of the package are arx, getsm, getsv and isat. The rst function estimates an AR-X model with log-ARCH-X errors. The second function undertakes GETS model selection of the mean specication of an arx object. The third function undertakes GETS model selection of the log-variance specication of an arx object. The fourth function undertakes GETS model selection of an indicator saturated mean specication. Examples of how LaTeX code of the estimation output can be generated is given, and the usage of two convenience functions for export of results to EViews and STATA are illustrated.
Pretis, F., Reade, J.J. & Sucarrat, G. (2016). 'gets: General-to-specific (GETS) modelling and indicator saturation methods'. R package version 0.8 (released 29 June 2016).