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Get the most appropriate autoregressive integrated moving average, generalized auto-regressive conditional heteroscedasticity and Markov switching GARCH model. For method details see Haas M, Mittnik S, Paolella MS (2004). <doi:10.1093/jjfinec/nbh020>, Bollerslev T (1986). <doi:10.1016/0304-4076(86)90063-1>.
| Version: | 0.1.0 |
| Depends: | R (≥ 2.10) |
| Imports: | MSGARCH, forecast, rugarch |
| Published: | 2020-10-28 |
| DOI: | 10.32614/CRAN.package.SBAGM |
| Author: | Rajeev Ranjan Kumar [aut, cre], Girish Kumar Jha [aut, ths, ctb], Dwijesh C. Mishra [ctb], Neeraj Budhlakoti [ctb] |
| Maintainer: | Rajeev Ranjan Kumar <rrk.uasd at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | SBAGM results |
| Reference manual: | SBAGM.pdf |
| Package source: | SBAGM_0.1.0.tar.gz |
| Windows binaries: | r-devel: SBAGM_0.1.0.zip, r-release: SBAGM_0.1.0.zip, r-oldrel: SBAGM_0.1.0.zip |
| macOS binaries: | r-release (arm64): SBAGM_0.1.0.tgz, r-oldrel (arm64): SBAGM_0.1.0.tgz, r-release (x86_64): SBAGM_0.1.0.tgz, r-oldrel (x86_64): SBAGM_0.1.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.