Package: coconots 1.1.3

coconots: Convolution-Closed Models for Count Time Series

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 modelled 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) <doi:10.1111/j.1467-9892.2010.00697.x> and the model assessment tools are presented in Czado et al. (2009) <doi:10.1111/j.1541-0420.2009.01191.x>, Gneiting and Raftery (2007) <doi:10.1198/016214506000001437> and, Tsay (1992) <doi:10.2307/2347612>.

Authors:Manuel Huth [aut, cre], Robert C. Jung [aut], Andy Tremayne [aut]

coconots_1.1.3.tar.gz
coconots_1.1.3.zip(r-4.5)coconots_1.1.3.zip(r-4.4)coconots_1.1.3.zip(r-4.3)
coconots_1.1.3.tgz(r-4.4-x86_64)coconots_1.1.3.tgz(r-4.4-arm64)coconots_1.1.3.tgz(r-4.3-x86_64)coconots_1.1.3.tgz(r-4.3-arm64)
coconots_1.1.3.tar.gz(r-4.5-noble)coconots_1.1.3.tar.gz(r-4.4-noble)
coconots_1.1.3.tgz(r-4.4-emscripten)coconots_1.1.3.tgz(r-4.3-emscripten)
coconots.pdf |coconots.html
coconots/json (API)

# Install 'coconots' in R:
install.packages('coconots', repos = c('https://manuhuth.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/manuhuth/coconots/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • cuts - Time Series of Monthly Counts of Claimants Collecting Wage Loss Benefit for Injuries in the Workplace
  • downloads - Time Series of Daily Downloads of a TeX-Editor
  • goldparticle - Time Series of Gold particles Counts in a well-efined Colloidal Solution

On CRAN:

3.70 score 2 stars 4 scripts 266 downloads 10 exports 49 dependencies

Last updated 3 days agofrom:85f2d90ef9. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 20 2024
R-4.5-win-x86_64NOTENov 20 2024
R-4.5-linux-x86_64NOTENov 20 2024
R-4.4-win-x86_64NOTENov 20 2024
R-4.4-mac-x86_64NOTENov 20 2024
R-4.4-mac-aarch64NOTENov 20 2024
R-4.3-win-x86_64NOTENov 20 2024
R-4.3-mac-x86_64NOTENov 20 2024
R-4.3-mac-aarch64NOTENov 20 2024

Exports:autoplotcocoBootcocoPitcocoRegcocoResidcocoScorecocoSimcocoSocinstallJuliaPackagessetJuliaSeed

Dependencies:clicolorspacecurlfansifarverforecastfracdiffgenericsggplot2gluegtableHMMpaisobandjsonliteJuliaConnectoRlabelinglatticelifecyclelmtestmagrittrMASSMatrixmatrixStatsmgcvmunsellnlmennetnumDerivpillarpkgconfigquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangscalestibbletimeDatetseriesTTRurcautf8vctrsviridisLitewithrxtszoo