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Simulation, estimation and inference for univariate and multivariate 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; see Campos-Martins and Sucarrat (2024) <doi:10.18637/jss.v108.i09>. In the multivariate case, variances are estimated equation by equation and dynamic conditional correlations are allowed. The TV long-term component of the variance as in the multiplicative TV-GARCH model of Amado and Terasvirta (2013) <doi:10.1016/j.jeconom.2013.03.006> introduces non-stationarity whereas the GARCH-X short-term component describes conditional heteroscedasticity. Maximisation by parts leads to consistent and asymptotically normal estimates.
| Version: | 2.4.2 |
| Depends: | R (≥ 3.5.0), garchx, zoo, numDeriv |
| Published: | 2024-04-04 |
| Author: | Susana Campos-Martins [aut, cre], Genaro Sucarrat [ctb] |
| Maintainer: | Susana Campos-Martins <scmartins at ucp.pt> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://sites.google.com/site/susanacamposmartins |
| NeedsCompilation: | no |
| Citation: | tvgarch citation info |
| Materials: | NEWS |
| CRAN checks: | tvgarch results |
| Reference manual: | tvgarch.pdf |
| Package source: | tvgarch_2.4.2.tar.gz |
| Windows binaries: | r-devel: tvgarch_2.4.2.zip, r-release: tvgarch_2.4.2.zip, r-oldrel: tvgarch_2.4.2.zip |
| macOS binaries: | r-release (arm64): tvgarch_2.4.2.tgz, r-oldrel (arm64): tvgarch_2.4.2.tgz, r-release (x86_64): tvgarch_2.4.2.tgz, r-oldrel (x86_64): tvgarch_2.4.2.tgz |
| Old sources: | tvgarch archive |
| Reverse suggests: | garchx |
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