Package: mixpoissonreg 1.0.0
mixpoissonreg: Mixed Poisson Regression for Overdispersed Count Data
Fits mixed Poisson regression models (Poisson-Inverse Gaussian or Negative-Binomial) on data sets with response variables being count data. The models can have varying precision parameter, where a linear regression structure (through a link function) is assumed to hold on the precision parameter. The Expectation-Maximization algorithm for both these models (Poisson Inverse Gaussian and Negative Binomial) is an important contribution of this package. Another important feature of this package is the set of functions to perform global and local influence analysis. See Barreto-Souza and Simas (2016) <doi:10.1007/s11222-015-9601-6> for further details.
Authors:
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mixpoissonreg.pdf |mixpoissonreg.html✨
mixpoissonreg/json (API)
NEWS
# Install 'mixpoissonreg' in R: |
install.packages('mixpoissonreg', repos = c('https://vpnsctl.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/vpnsctl/mixpoissonreg/issues
Pkgdown site:https://vpnsctl.github.io
- Attendance - Attendance Records data set
count-datadiagnosticsinfluence-analysislocal-influencenegative-binomial-regressionpoisson-inverse-gaussian-regression
Last updated 4 years agofrom:03573c0a90. Checks:9 OK. Indexed: yes.
Target | Result | Latest binary |
---|---|---|
Doc / Vignettes | OK | Mar 11 2025 |
R-4.5-win | OK | Mar 11 2025 |
R-4.5-mac | OK | Mar 11 2025 |
R-4.5-linux | OK | Mar 11 2025 |
R-4.4-win | OK | Mar 11 2025 |
R-4.4-mac | OK | Mar 11 2025 |
R-4.4-linux | OK | Mar 11 2025 |
R-4.3-win | OK | Mar 11 2025 |
R-4.3-mac | OK | Mar 11 2025 |
Exports:augmentautoplotglancelocal_influencelocal_influence_autoplotlocal_influence_benchmarkslocal_influence_plotmixpoissonregmixpoissonreg.fitmixpoissonregMLmixpoissonregML.fittidytidy_local_influence
Dependencies:clicolorspacedplyrfansifarverFormulagamlssgamlss.datagamlss.distgenericsggplot2ggrepelgluegridExtragtableisobandlabelinglatticelifecyclelmtestmagrittrMASSMatrixmgcvmunsellnlmepbapplypillarpkgconfigR6RColorBrewerRcppRcppArmadilloRcppParallelRfastrlangscalesstatmodsurvivaltibbletidyselectutf8vctrsviridisLitewithrziggzoo
Analyzing overdispersed count data with the mixpoissonreg package
Rendered fromtutorial-mixpoissonreg.Rmd
usingknitr::rmarkdown
on Mar 11 2025.Last update: 2021-03-12
Started: 2020-12-22
Building and customizing base-R diagnostic plots with the mixpoissonreg package
Rendered fromplots-mixpoissonreg.Rmd
usingknitr::rmarkdown
on Mar 11 2025.Last update: 2021-03-05
Started: 2020-12-22
Building and customizing ggplot2-based diagnostic plots with the mixpoissonreg package
Rendered fromggplot2-plots-mixpoissonreg.Rmd
usingknitr::rmarkdown
on Mar 11 2025.Last update: 2021-03-05
Started: 2021-02-27
Confidence and prediction intervals with the mixpoissonreg package
Rendered fromintervals-mixpoissonreg.Rmd
usingknitr::rmarkdown
on Mar 11 2025.Last update: 2021-03-05
Started: 2020-12-22
Global and local influence analysis with the mixpoissonreg package
Rendered frominfluence-mixpoissonreg.Rmd
usingknitr::rmarkdown
on Mar 11 2025.Last update: 2021-03-05
Started: 2020-12-22
Introduction to mixpoissonreg
Rendered frommixpoissonreg.Rmd
usingknitr::rmarkdown
on Mar 11 2025.Last update: 2021-03-05
Started: 2020-12-23
Maximum-likelihood estimation with the mixpoissonreg package
Rendered fromml-mixpoissonreg.Rmd
usingknitr::rmarkdown
on Mar 11 2025.Last update: 2021-03-05
Started: 2020-12-22
mixpoissonreg in the tidyverse
Rendered fromtidyverse-mixpoissonreg.Rmd
usingknitr::rmarkdown
on Mar 11 2025.Last update: 2021-03-05
Started: 2020-12-22