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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. Models with the identity and with the logarithmic link function are allowed. The conditional distribution can be Poisson or Negative Binomial.

Version: 1.4.3
Imports: parallel, ltsa
Suggests: Matrix, xtable, gamlss.data, surveillance
Published: 2020-09-08
DOI: 10.32614/CRAN.package.tscount
Author: Tobias Liboschik [aut, cre], Roland Fried [aut], Konstantinos Fokianos [aut], Philipp Probst [aut], Jonathan Rathjens [ctb]
Maintainer: Tobias Liboschik <liboschik at statistik.tu-dortmund.de>
License: GPL-2 | GPL-3
URL: http://tscount.r-forge.r-project.org
NeedsCompilation: no
Citation: tscount citation info
Materials: NEWS
In views: TimeSeries
CRAN checks: tscount results

Documentation:

Reference manual: tscount.pdf
Vignettes: tscount: An R Package for Analysis of Count Time Series Following Generalized Linear Models

Downloads:

Package source: tscount_1.4.3.tar.gz
Windows binaries: r-devel: tscount_1.4.3.zip, r-release: tscount_1.4.3.zip, r-oldrel: tscount_1.4.3.zip
macOS binaries: r-release (arm64): tscount_1.4.3.tgz, r-oldrel (arm64): tscount_1.4.3.tgz, r-release (x86_64): tscount_1.4.3.tgz, r-oldrel (x86_64): tscount_1.4.3.tgz
Old sources: tscount archive

Reverse dependencies:

Reverse depends: fableCount

Linking:

Please use the canonical form https://CRAN.R-project.org/package=tscount to link to this page.

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.