Package: MixedPoisson 2.0
Alicja Wolny-Dominiak
MixedPoisson: Mixed Poisson Models
The estimation of the parameters in mixed Poisson models.
Authors:
MixedPoisson_2.0.tar.gz
MixedPoisson_2.0.tar.gz(r-4.5-noble)MixedPoisson_2.0.tar.gz(r-4.4-noble)
MixedPoisson_2.0.tgz(r-4.4-emscripten)MixedPoisson_2.0.tgz(r-4.3-emscripten)
MixedPoisson.pdf |MixedPoisson.html✨
MixedPoisson/json (API)
# Install 'MixedPoisson' in R: |
install.packages('MixedPoisson', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 8 years agofrom:d726290616. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 14 2024 |
R-4.5-linux | OK | Dec 14 2024 |
Exports:est.deltaest.gammaest.nuGamma.densityinvGauss.densitylambda_m_steplambda_startll.gammall.invGaussll.lognormlognorm.densitypg.distpl.distpseudo_values
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Mixed Poisson Models | MixedPoisson-package MixedPoisson2 |
Estimation of delta parameter of inverse-Gaussian distribution | est.delta |
Estimation of gamma parameter of Gamma distribution | est.gamma |
Estimation of nu parameter of log-normal distribution | est.nu |
Gamma density | Gamma.density |
inverse-Gaussian Density | invGauss.density |
Estimation of Lambda in M-step - Expectation-Maximization (EM) algorithm | lambda_m_step |
Estimation of starting lambda in Expectation-Maximization (EM) algorithm | lambda_start |
Gamma Log-likelihood | ll.gamma |
Inverse-Gaussian Log-likelihood | ll.invGauss |
Log-normal Log-likelihood | ll.lognorm |
Log-normal Density | lognorm.density |
Poisson-Gamma Distribution (Negative-Binomial) | pg.dist |
Poisson-Lindley Distribution | pl.dist |
Pseudo values - Expectation-Maximization (EM) algorithm | pseudo_values |