Package: tscount 1.4.4
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Tobias Liboschik
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.
Authors:
tscount_1.4.4.tar.gz
tscount_1.4.4.zip(r-4.5)tscount_1.4.4.zip(r-4.4)tscount_1.4.4.zip(r-4.3)
tscount_1.4.4.tgz(r-4.4-any)tscount_1.4.4.tgz(r-4.3-any)
tscount_1.4.4.tar.gz(r-4.5-noble)tscount_1.4.4.tar.gz(r-4.4-noble)
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tscount.pdf |tscount.html✨
tscount/json (API)
NEWS
# Install 'tscount' in R: |
install.packages('tscount', repos = c('https://r-forge.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://r-forge.r-project.org/projects/tscount
Last updated 1 years agofrom:d4774dc5aa. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Sep 01 2024 |
R-4.5-win | OK | Sep 01 2024 |
R-4.5-linux | OK | Sep 01 2024 |
R-4.4-win | OK | Sep 01 2024 |
R-4.4-mac | OK | Sep 01 2024 |
R-4.3-win | OK | Sep 01 2024 |
R-4.3-mac | OK | Sep 01 2024 |
Exports:ardistrcheckdistrddistringarch.acfingarch.meaningarch.varinterv_covariateinterv_detectinterv_multipleinterv_testinvertinfomarcalpdistrpitqdistrQICrdistrscoringsddistrsetsglmtsglm.meanfittsglm.sim
Dependencies:ltsa