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tscount: Analysis of Count Time Series
Likelihood-based methods for model fitting and assessment, prediction and intervention analysis of count time series following generalized linear models are provided, see Liboschik et al. (2017) <doi:10.18637/jss.v082.i05>. Models with the identity and with the logarithmic link function are allowed. The conditional distribution can be Poisson or Negative Binomial.
Getting started
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Package details |
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| Author | Tobias Liboschik [aut, cre], Roland Fried [aut], Konstantinos Fokianos [aut], Philipp Probst [aut], Jonathan Rathjens [ctb], Nicolò Rubattu [ctb] |
| Maintainer | Tobias Liboschik <liboschik@statistik.tu-dortmund.de> |
| License | GPL-2 | GPL-3 |
| Version | 1.4.4 |
| URL | http://tscount.r-forge.r-project.org |
| Package repository | View on R-Forge |
| Installation |
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