Package: ewp 0.1.1

ewp: An Empirical Model for Underdispersed Count Data

Count regression models for underdispersed small counts (lambda < 20) based on the three-parameter exponentially weighted Poisson distribution of Ridout & Besbeas (2004) <doi:10.1191/1471082X04st064oa>.

Authors:Philipp Boersch-Supan [aut, cre], James Clarke [aut]

ewp_0.1.1.tar.gz
ewp_0.1.1.zip(r-4.5)ewp_0.1.1.zip(r-4.4)ewp_0.1.1.zip(r-4.3)
ewp_0.1.1.tgz(r-4.4-x86_64)ewp_0.1.1.tgz(r-4.4-arm64)ewp_0.1.1.tgz(r-4.3-x86_64)ewp_0.1.1.tgz(r-4.3-arm64)
ewp_0.1.1.tar.gz(r-4.5-noble)ewp_0.1.1.tar.gz(r-4.4-noble)
ewp_0.1.1.tgz(r-4.4-emscripten)ewp_0.1.1.tgz(r-4.3-emscripten)
ewp.pdf |ewp.html✨
ewp/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/pboesu/ewp/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

4 exports 1.18 score 2 dependencies 6 scripts 148 downloads

Last updated 3 months agofrom:886f4fab11. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 24 2024
R-4.5-win-x86_64OKAug 24 2024
R-4.5-linux-x86_64OKAug 24 2024
R-4.4-win-x86_64OKAug 24 2024
R-4.4-mac-x86_64OKAug 24 2024
R-4.4-mac-aarch64OKAug 24 2024
R-4.3-win-x86_64OKAug 24 2024
R-4.3-mac-x86_64OKAug 24 2024
R-4.3-mac-aarch64OKAug 24 2024

Exports:dewp3dewp3_cppewp_regrewp3

Dependencies:BHRcpp