hurdletest: Testing for the Presence of a Zero Hurdle

Description

Wald test of the null hypothesis that no zero hurdle is required in hurdle regression models for count data.

Usage

hurdletest(object, ...)

Value

An object of class "anova" as returned by linearHypothesis.

Arguments

object: A fitted model object of class "hurdle" as returned by hurdle, see details for more information.
...: arguments passed to linearHypothesis.

Author

Achim Zeileis <Achim.Zeileis@R-project.org>

Details

If the same count distribution and the same set of regressors is used in the hurdle model for both, the count component and the zero hurdle component, then a test of pairwise equality between all coefficients from the two components assesses the null hypothesis that no hurdle is needed in the model.

The function hurdletest is a simple convenience interface to the function linearHypothesis from the car packages that can be employed to carry out a Wald test for this hypothesis.

References

Cameron, A. Colin and Pravin K. Trivedi. 1998. Regression Analysis of Count Data. New York: Cambridge University Press.

Cameron, A. Colin and Pravin K. Trivedi 2005. Microeconometrics: Methods and Applications. Cambridge: Cambridge University Press.

Examples

Run this code

data("bioChemists", package = "pscl")
fm <- hurdle(art ~ ., data = bioChemists, dist = "negbin", zero = "negbin")
hurdletest(fm)

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