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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", "1.1.3")



Attach the package and use:
library("coconots")
Maintained by
Manuel Huth
[Scholar Profile | Author Map]
First Published: 2023-03-13
Latest Update: 2023-10-01
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 1.1.3, https://cran.r-project.org/web/packages/coconots. Accessed 29 Mar. 2025.
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)
Other packages that cited coconots R package
View coconots citation profile
Other R packages that coconots depends, imports, suggests or enhances
Complete documentation for coconots
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