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:
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')) |
Bug tracker:https://github.com/pboesu/ewp/issues
Datasets:
- linnet - Linnet clutch sizes
Last updated 5 months agofrom:886f4fab11. Checks:OK: 9. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 22 2024 |
R-4.5-win-x86_64 | OK | Nov 22 2024 |
R-4.5-linux-x86_64 | OK | Nov 22 2024 |
R-4.4-win-x86_64 | OK | Nov 22 2024 |
R-4.4-mac-x86_64 | OK | Nov 22 2024 |
R-4.4-mac-aarch64 | OK | Nov 22 2024 |
R-4.3-win-x86_64 | OK | Nov 22 2024 |
R-4.3-mac-x86_64 | OK | Nov 22 2024 |
R-4.3-mac-aarch64 | OK | Nov 22 2024 |
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Extract coefficients | coef.ewp |
Probability mass function of the three-parameter EWP | dewp3 |
Probability mass function of the three-parameter EWP | dewp3_cpp |
Exponentially weighted Poisson regression model | ewp_reg |
Extract fitted values | fitted.ewp |
Linnet clutch sizes | linnet |
Extract log likelihood | logLik.ewp |
Predict from fitted model | predict.ewp |
Print ewp model object | print.ewp |
Print ewp model summary | print.summary.ewp |
Random samples from the three-parameter EWP | rewp3 |
simulate from fitted model | simulate.ewp |
Model summary | summary.ewp |
Extract estimated variance-covariance matrix | vcov.ewp |