General-to-Specific (GETS) modelling provides a comprehensive, systematic and cumulative approach to modelling that is ideally suited for conditional forecasting and counterfactual analysis, whereas Indicator Saturation (ISAT) is a powerful and flexible approach to the detection and estimation of structural breaks (e.g. changes in parameters), and to the detection of outliers. To these ends, multi-path backwards elimination, single and multiple hypothesis tests on the coefficients, diagnostics tests and goodness-of-fit measures are combined to produce a parsimonious final model. In many situations a specific model or estimator is needed, a specific set of diagnostics tests may be required, or a specific fit criterion is preferred. In these situations, if the combination of estimator/model, diagnostics tests and fit criterion is not offered in a pre-programmed way by publicly available software, then the implementation of user-specified GETS and ISAT methods puts a large programming-burden on the user. Generic functions and procedures that facilitate the implementation of user-specified GETS and ISAT methods for specific problems can therefore be of great benefit. The R package gets is the first software – both inside and outside the R universe – to provide a complete set of facilities for user-specified GETS and ISAT methods: User-specified model/estimator, user-specified diagnostics and user-specified goodness-of-fit criteria. The aim of this article is to illustrate how user-specified GETS and ISAT methods can be implemented with the R package gets.
Supplementary materials are available in addition to this article. It can be downloaded at RJ-2021-024.zip
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For attribution, please cite this work as
Sucarrat, "User-Specified General-to-Specific and Indicator Saturation Methods", The R Journal, 2021
BibTeX citation
@article{RJ-2021-024,
author = {Sucarrat, Genaro},
title = {User-Specified General-to-Specific and Indicator Saturation Methods},
journal = {The R Journal},
year = {2021},
note = {https://doi.org/10.32614/RJ-2021-024},
doi = {10.32614/RJ-2021-024},
volume = {12},
issue = {2},
issn = {2073-4859},
pages = {251-265}
}