flexCountReg0.1.1 package

Estimation of a Variety of Count Regression Models

COMDistribution

Conway-Maxwell-Poisson (COM) Distribution

cor2cov

Generate a covariance matrix using a correlation matrix and vector of ...

corr_haltons

Generate Correlated Random Variables Using Halton or Scrambled Halton ...

countreg

Count regression models

countreg.rp

Random Parameters Count Regression Models

cureplot

Cumulative Residuals (CURE) Plot for Count Models

flexCountReg-class

flexCountReg Class

Generalized-Waring

Generalized Waring Distribution

halton_dists

Generate pseudo-random draws from specified distributions using Halton...

invgamma

Inverse Gamma Distribution

Lindley

One-Parameter Lindley Distribution

mae

Calculate Mean Absolute Error (MAE)

mgf_lognormal

Moment Generating Function for a Lognormal Distribution

myAIC

Calculate Akaike Information Criterion (AIC)

myBIC

Calculate Bayesian Information Criterion (BIC)

NegativeBinomialLindley

Poisson-Lindley-Gamma (Negative Binomial-Lindley) Distribution

poisLindRE

Function for estimating a Random Effects Poisson-Lindley regression mo...

PoissonGeneralizedExponential

Poisson-Generalized-Exponential Distribution

PoissonInverseGamma

Poisson-Inverse-Gamma Distribution

PoissonInverseGaussian

Poisson-Inverse-Gaussian Distribution

PoissonLindley

Poisson-Lindley Distribution

PoissonLindleyLognormal

Poisson-Lindley-Lognormal Distribution

PoissonLognormal

Poisson-Lognormal Distribution

PoissonWeibull

Poisson-Weibull Distribution Functions

predict.flexCountReg

Predictions for flexCountReg models

regCompTable

Create a Table Comparing Regression Models with AIC, BIC, and McFadden...

regCompTest

Compare Regression Models with Likelihood Ratio Test, AIC, and BIC

renb

Estimate a Random Effects Negative Binomial regression model

rmse

Calculate Root Mean Squared Error (RMSE)

SichelDistribution

Sichel Distribution

summary.flexCountReg

Custom summary method for flexCountReg models

tidy.flexCountReg

Tidy a flexCountReg object

Triangular

Triangle Distribution

Download source packageRead PDF manual

An implementation of multiple regression models for count data. These include various forms of the negative binomial (NB-1, NB-2, NB-P, generalized negative binomial, etc.), Poisson-Lognormal, other compound Poisson distributions, the Generalized Waring model, etc. Information on the different forms of the negative binomial are described by Greene (2008) <doi:10.1016/j.econlet.2007.10.015>. For treatises on count models, see Cameron and Trivedi (2013) <doi:10.1017/CBO9781139013567> and Hilbe (2012) <doi:10.1017/CBO9780511973420>. For the implementation of under-reporting in count models, see Wood et al. (2016) <doi:10.1016/j.aap.2016.06.013>. For prediction methods in random parameter models, see Wood and Gayah (2025) <doi:10.1016/j.aap.2025.108147>. For estimating random parameters using maximum simulated likelihood, see Greene and Hill (2010) <doi:10.1108/S0731-9053(2010)26>; Gourieroux and Monfort (1996) <doi:10.1093/0198774753.001.0001>; or Hensher et al. (2015) <doi:10.1017/CBO9781316136232>.