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Routines for fitting and simulating data under autoregressive fractionally integrated moving average (ARFIMA) models, without the constraint of covariance stationarity. Two fitting methods are implemented, a pseudo-maximum likelihood method and a minimum distance estimator. Mayoral, L. (2007) <doi:10.1111/j.1368-423X.2007.00202.x>. Beran, J. (1995) <doi:10.1111/j.2517-6161.1995.tb02054.x>.
| Version: | 0.2.0.0 |
| Depends: | R (≥ 3.6.0) |
| Published: | 2020-08-06 |
| Author: | Benjamin Groebe [aut, cre] |
| Maintainer: | Benjamin Groebe <ben.groebe at gmail.com> |
| License: | GPL (≥ 3) |
| NeedsCompilation: | no |
| In views: | TimeSeries |
| CRAN checks: | nsarfima results |
| Reference manual: | nsarfima.pdf |
| Package source: | nsarfima_0.2.0.0.tar.gz |
| Windows binaries: | r-devel: nsarfima_0.2.0.0.zip, r-release: nsarfima_0.2.0.0.zip, r-oldrel: nsarfima_0.2.0.0.zip |
| macOS binaries: | r-release (arm64): nsarfima_0.2.0.0.tgz, r-oldrel (arm64): nsarfima_0.2.0.0.tgz, r-release (x86_64): nsarfima_0.2.0.0.tgz, r-oldrel (x86_64): nsarfima_0.2.0.0.tgz |
| Old sources: | nsarfima archive |
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