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:Alexandre B. Simas [aut, cre], Wagner Barreto-Souza [aut]

mixpoissonreg_1.0.0.tar.gz
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mixpoissonreg_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
mixpoissonreg/json (API)

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

Bug tracker:https://github.com/vpnsctl/mixpoissonreg/issues

Datasets:

On CRAN:

Conda:

count-datadiagnosticsinfluence-analysislocal-influencenegative-binomial-regressionpoisson-inverse-gaussian-regression

5.35 score 2 stars 28 scripts 403 downloads 13 exports 45 dependencies

Last updated from:03573c0a90. Checks:2 NOTE, 7 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develNOTE200
source / vignettesOK493
linux-releaseOK217
macos-releaseOK236
macos-oldrelOK283
windows-develNOTE229
windows-releaseOK211
windows-oldrelOK179
wasm-releaseOK134

Exports:augmentautoplotglancelocal_influencelocal_influence_autoplotlocal_influence_benchmarkslocal_influence_plotmixpoissonregmixpoissonreg.fitmixpoissonregMLmixpoissonregML.fittidytidy_local_influence

Dependencies:clicpp11dplyrfarverFormulagamlssgamlss.datagamlss.distgenericsggplot2ggrepelgluegridExtragtableisobandlabelinglatticelifecyclelmtestmagrittrMASSMatrixnlmepbapplypillarpkgconfigR6RColorBrewerRcppRcppArmadilloRcppParallelRfastrlangS7scalesstatmodsurvivaltibbletidyselectutf8vctrsviridisLitewithrziggzoo

Analyzing overdispersed count data with the mixpoissonreg package
Description of the dataset | Model fitting and inference | Residual analysis | Influence analysis
Rendered fromtutorial-mixpoissonreg.Rmdusingknitr::rmarkdown

Last update: 2021-03-12
Started: 2020-12-22

Global and local influence analysis with the mixpoissonreg package
Global Influence | hatvalues method | cooks.distance method | Cook's distance | generalized Cook's distance and Q-displacement | Likelihood displacement | influence method | Global influence plots | Local Influence | Curvature | Direction | Perturbation | Parameters | Perturbation schemes with respect to a subset of the covariates | Local influence plots | References
Rendered frominfluence-mixpoissonreg.Rmdusingknitr::rmarkdown

Last update: 2021-03-05
Started: 2020-12-22

mixpoissonreg in the tidyverse
augment, glance and tidy methods | augment | glance | tidy | tidy_local_influence and local_influence_benchmarks methods | autoplot and local_influence_autoplot methods
Rendered fromtidyverse-mixpoissonreg.Rmdusingknitr::rmarkdown

Last update: 2021-03-05
Started: 2020-12-22

Building and customizing base-R diagnostic plots with the mixpoissonreg package
base-R diagnostic plots | Choosing plots | Titles and subtitles | Colors, sizes, point types and line types | Points to be identified
Rendered fromplots-mixpoissonreg.Rmdusingknitr::rmarkdown

Last update: 2021-03-05
Started: 2020-12-22

Building and customizing ggplot2-based diagnostic plots with the mixpoissonreg package
ggplot2-based diagnostic plots | Choosing plots | Titles and subtitles | Colors, sizes, point types and line types | Points to be identified | Multiple plots
Rendered fromggplot2-plots-mixpoissonreg.Rmdusingknitr::rmarkdown

Last update: 2021-03-05
Started: 2021-02-27

Confidence and prediction intervals with the mixpoissonreg package
Standard errors for the means | Standard errors for the means using the predict method | Standard errors for the means using the augment method | Confidence intervals for the means | Confidence intervals for the means using the predict method | Confidence intervals for the means using the augment method | Prediction intervals for the response variables | Prediction intervals for the response variables using the predict method | Prediction intervals for the response variables using the augment method
Rendered fromintervals-mixpoissonreg.Rmdusingknitr::rmarkdown

Last update: 2021-03-05
Started: 2020-12-22

Maximum-likelihood estimation with the mixpoissonreg package
Fitting mixpoissonreg models via direct maximization of the likelihood function | Obtaining estimates without formulas
Rendered fromml-mixpoissonreg.Rmdusingknitr::rmarkdown

Last update: 2021-03-05
Started: 2020-12-22

Introduction to mixpoissonreg
What is mixpoissonreg for? | Why use the mixpoissonreg package? | glm-like functions to fit and analyze fitted models | Useful plots for fitted models available using R's base graphics or ggplot2 | Estimation of parameters via EM-algorithm | Easy to do inference on fitted models with help of lmtest package | Regression structure for the precision parameter | Several global and local influence measures implemented (along with corresponding plots) | Compatibility with the tidyverse
Rendered frommixpoissonreg.Rmdusingknitr::rmarkdown

Last update: 2021-03-05
Started: 2020-12-23

Readme and manuals

Help Manual

Help pageTopics
Attendance Records data setAttendance
Augment data with information from a 'mixpoissonreg' objectaugment augment.mixpoissonreg
Autoplot Method for 'mixpoissonreg' Objectsautoplot autoplot.mixpoissonreg
Coef Method for 'mixpoissonreg' Objects.coef.mixpoissonreg
Fitted Method for 'mixpoissonreg' Objectsfitted.mixpoissonreg
Glance at a 'mixpoissonreg' objectglance glance.mixpoissonreg
Global Influence Diagnostics for Mixed Poisson Regression Modelscooks.distance.mixpoissonreg hatvalues.mixpoissonreg influence.mixpoissonreg
Local Influence Diagnosticslocal_influence local_influence_plot
Local Influence Autoplots for 'mixpoissonreg' Objectslocal_influence_autoplot.mixpoissonreg
Local Influence Plot Diagnostics for Mixed Poisson Regression Modelslocal_influence_plot.mixpoissonreg
Local Influence Diagnostics for Mixed Poisson Regression Modelslocal_influence.mixpoissonreg
logLik Method for 'mixpoissonreg' ObjectslogLik.mixpoissonreg
Mixed Poisson Regression for Overdispersed Count Datamixpoissonreg mixpoissonreg.fit
Maximum Likelihood Mixed Poisson Regression Models for Overdispersed Count DatamixpoissonregML mixpoissonregML.fit
Plot Diagnostics for 'mixpoissonreg' Objectsplot.mixpoissonreg
Predict Method for 'mixpoissonreg' Objectspredict.mixpoissonreg
Residuals Method for 'mixpoissonreg' Objectsresiduals.mixpoissonreg
Summary Method for 'mixpoissonreg' Objects.summary.mixpoissonreg
Tidy Functions for Local Influence Diagnosticslocal_influence_autoplot local_influence_benchmarks tidy_local_influence
Tidy Functions for Local Influence Diagnostics for 'mixpoissonreg' Objectslocal_influence_benchmarks.mixpoissonreg tidy_local_influence.mixpoissonreg
Tidy a 'mixpoissonreg' objecttidy tidy.mixpoissonreg
Calculate Variance-Covariance Matrix for 'mixpoissonreg' Objectsvcov.mixpoissonreg