Package: ewp 0.1.1
Philipp Boersch-Supan
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.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
| # Installewp in R: |
| install.packages('ewp',repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Datasets:
- linnet - Linnet clutch sizes
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 9 days agofrom:1f7ed181e8
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 |
