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coconots  

Convolution-Closed Models for Count Time Series
View on CRAN: Click here


Download and install coconots package within the R console
Install from CRAN:
install.packages("coconots")

Install from Github:
library("remotes")
install_github("cran/coconots")

Install by package version:
library("remotes")
install_version("coconots", "2.0.2")



Attach the package and use:
library("coconots")
Maintained by
Manuel Huth
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-03-13
Latest Update: 2025-07-24
Description:
Useful tools for fitting, validating, and forecasting of practical convolution-closed time series models for low counts are provided. Marginal distributions of the data can be modeled via Poisson and Generalized Poisson innovations. Regression effects can be modelled via time varying innovation rates. The models are described in Jung and Tremayne (2011) and the model assessment tools are presented in Czado et al. (2009) , Gneiting and Raftery (2007) and, Tsay (1992) .
How to cite:
Manuel Huth (2023). coconots: Convolution-Closed Models for Count Time Series. R package version 2.0.2, https://cran.r-project.org/web/packages/coconots. Accessed 25 Jun. 2026.
Previous versions and publish date:
1.1.1 (2023-03-29 10:40), 1.1.2 (2023-08-19 12:12), 1.1.3 (2023-10-01 17:10), 1.1 (2023-03-13 14:30), 2.0.0 (2025-03-22 08:50), 2.0.1 (2025-07-24 14:00), 2.0.2 (2025-08-22 17:30)
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