Simulation, estimation and inference for TV(s)-GARCH(p,q,r)-X models, where s indicates the number and shape of the transition functions, p is the ARCH order, q is the GARCH order, r is the asymmetry order, and 'X' indicates that covariates can be included. The TV long-term component, as in the multiplicative TV-GARCH model of Amado and Ter\"asvirta (2013) <doi:10.1016/j.jeconom.2013.03.006>, introduces non-stationarity in the variance process, where the GARCH-X short-term component describes conditional heteroscedasticity. Maximisation by parts leads to consistent and asymptotically normal estimates.
| Version: | 1.0 |
| Depends: | R (≥ 3.5.0), garchx, hier.part, matrixStats, numDeriv, zoo |
| Published: | 2021-02-05 |
| Author: | Susana Campos-Martins [aut, cre], Genaro Sucarrat [ctb] |
| Maintainer: | Susana Campos-Martins <susana.martins at nuffield.ox.ac.uk> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://sites.google.com/site/susanacamposmartins/ |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | tvgarch results |
| Reference manual: | tvgarch.pdf |
| Package source: | tvgarch_1.0.tar.gz |
| Windows binaries: | r-devel: tvgarch_1.0.zip, r-release: tvgarch_1.0.zip, r-oldrel: tvgarch_1.0.zip |
| macOS binaries: | r-release: tvgarch_1.0.tgz, r-oldrel: tvgarch_1.0.tgz |
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