poisreg: Poisson regression

In micsr: Microeconometrics with R

Poisson regression

Description

A unified interface to perform Poisson, Negbin and log-normal Poisson models

Usage

poisreg(
  formula,
  data,
  weights,
  subset,
  na.action,
  offset,
  contrasts = NULL,
  start = NULL,
  mixing = c("none", "gamma", "lognorm"),
  vlink = c("nb1", "nb2"),
  opt = c("bfgs", "nr", "newton"),
  maxit = 100,
  trace = 0,
  check_gradient = FALSE,
  ...
)

## S3 method for class 'poisreg'
scoretest(object, ..., vcov = NULL)

## S3 method for class 'poisreg'
residuals(object, ..., type = c("deviance", "pearson", "response"))

Arguments

formula	a symbolic description of the model, (for the count component and for the selection equation)
data	a data frame
subset, weights, na.action, offset, contrasts	see stats::lm,
start	a vector of starting values
mixing	the mixing distribution, one of "none", "gamma" and "lognorm"
vlink	one of "nb1" and "nb2"
opt	optimization method
maxit	maximum number of iterations
trace	printing of intermediate result
check_gradient	if TRUE the numeric gradient and hessian are computed and compared to the analytical gradient and hessian
...	further arguments
object	a poisreg object
vcov	the covariance matrix estimator to use for the score test
type	the type of residuals for the residuals method

Value

an object of class c("poisreg", "micsr"), see micsr::micsr for further details.

Examples

nb1 <- poisreg(trips ~ workschl + size + dist + smsa + fulltime + distnod +
               realinc + weekend + car, trips, mixing = "gamma", vlink = "nb1")

micsr documentation built on June 8, 2025, 9:31 p.m.