summary.hurdle {pscl}R Documentation

Summarzing Hurdle Regression Models for Count Data

Description

summary methods for class "hurdle"

Usage

## S3 method for class 'hurdle':
summary(object,...)

## S3 method for class 'summary.hurdle':
print(x, digits = max(3,getOption("digits")-3), ...)

Arguments

object object inheriting from class "hurdle"
x an object of class "summary.hurdle", usually a result of a call to summary.hurdle
digits the number of significant digits to use when printing
... further arguments passed to or from other methods

Details

print.summary.hurdle tries to be smart about formatting the display of the MLEs, standard errors, etc, essentially using the same code as appears in link{print.summary.lm}

Value

The function summary.hurdle computes and returns a list of summary statistics from the zero-inflated regression model, including

coefficents a matrix, with columns for the MLEs, their standard errors, z-statistic, and corresponding (two-sided) p-value.
vc The estimated variance-covariance matrix of the MLEs
beta The MLEs from the count component of the model
gamma The MLEs from the hurdle component of the model
theta If a negative binomial count model is fit, the MLE of the over-dispersion parameter
llh The value of the log-likelihood function at the MLEs

Author(s)

Simon Jackman <jackman@stanford.edu>

See Also

hurdle

Examples

data(bioChemists)
hp <- hurdle(count=art ~ .,
              x = ~ fem + mar + kid5 + phd + ment,
              z = ~ fem + mar + kid5 + phd + ment,
              data=bioChemists,trace=TRUE)
summary(hp)

hnb <- hurdle(count=art ~ .,
              x = ~ fem + mar + kid5 + phd + ment,
              z = ~ fem + mar + kid5 + phd + ment,
              dist="negbin",
              data=bioChemists,trace=TRUE)
summary(hnb)

[Package pscl version 0.52 Index]