A method for modeling robust generalized autoregressive conditional heteroskedasticity (Garch) (1,1) processes, providing robustness toward additive outliers instead of innovation outliers. This work is based on the methodology described by Muler and Yohai (2008) <doi:10.1016/j.jspi.2007.11.003>.
| Version: | 0.4.2 |
| Depends: | R (≥ 4.3.0) |
| Imports: | Rsolnp, nloptr, rugarch, zoo, xts |
| Suggests: | rmarkdown, testthat, PCRA |
| Published: | 2025-04-28 |
| DOI: | 10.32614/CRAN.package.robustGarch |
| Author: | Echo Liu [aut, cre], Daniel Xia [aut], R. Douglas Martin [aut] |
| Maintainer: | Echo Liu <yuhong.echo.liu at gmail.com> |
| BugReports: | https://github.com/EchoRLiu/robustGarch/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/EchoRLiu/robustGarch |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | robustGarch results |
| Reference manual: | robustGarch.pdf |
| Package source: | robustGarch_0.4.2.tar.gz |
| Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: not available |
| macOS binaries: | r-release (arm64): robustGarch_0.4.2.tgz, r-oldrel (arm64): robustGarch_0.4.2.tgz, r-release (x86_64): robustGarch_0.4.2.tgz, r-oldrel (x86_64): robustGarch_0.4.2.tgz |
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