Smooth Tests for the Zero‐Inflated Poisson Distribution

In this article we construct three smooth goodness‐of‐fit tests for testing for the zero‐inflated Poisson (ZIP) distribution against general smooth alternatives in the sense of Neyman. We apply our tests to a data set previously claimed to be ZIP distributed, and show that the ZIP is not a good mode...

Full description

Saved in:
Bibliographic Details
Published in:Biometrics 2005-09, Vol.61 (3), p.808-815
Main Authors: Thas, Olivier, Rayner, J. C. W.
Format: Article
Language:English
Subjects:
Animals
Biometrics
biometry
Computer Simulation
data collection
Data Interpretation, Statistical
Estimation methods
Estimators
Fetal Movement - physiology
Generalized score test
Hypothesis testing
Mathematical independent variables
Mathematical moments
Maximum likelihood estimation
Neyman smooth test
Null hypothesis
Orthonormal polynomials
Parametric models
Poisson Distribution
Polynomials
Regression Analysis
Sheep - embryology
Statistics
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this article we construct three smooth goodness‐of‐fit tests for testing for the zero‐inflated Poisson (ZIP) distribution against general smooth alternatives in the sense of Neyman. We apply our tests to a data set previously claimed to be ZIP distributed, and show that the ZIP is not a good model to describe the data. At rejection of the null hypothesis of ZIP, the individual components of the test statistic, which are directly related to interpretable parameters in a smooth model, may be used to gain insight into an alternative distribution.
ISSN:0006-341X
1541-0420
DOI:10.1111/j.1541-0420.2005.00351.x