Haslett, John and Parnell, Andrew and Sweeney, James
(2018)
A general framework for modelling zero inflation.
Working Paper.
arXiv.
Abstract
We propose a new framework for the modelling of count data exhibiting zero inflation (ZI). The main part of this framework includes a new and more general parameterisation for ZI models which naturally includes both over- and under-inflation. It further sheds new theoretical light on modelling and inference and permits a simpler alternative, which we term as multiplicative, in contrast to the dominant mixture and hurdle models. Our approach gives the statistician access to new types of ZI of which mixture and hurdle are special cases. We outline a simple parameterised modelling approach which can help to infer both ZI type and degree and provide an underlying treatment that shows that current ZI models are themselves typically within the exponential family, thus permitting much simpler theory, computation and classical inference. We outline some possibilities for a natural Bayesian framework for inference; and a rich basis for work on correlated ZI counts.
The present paper is an incomplete report on the underlying theory. A later version will include computational issues and provide further examples.
Item Type: |
Monograph
(Working Paper)
|
Keywords: |
count data; zero inflation; |
Academic Unit: |
Faculty of Science and Engineering > Research Institutes > Hamilton Institute |
Item ID: |
10257 |
Identification Number: |
1805.00555 [stat.ME] |
Depositing User: |
Andrew Parnell
|
Date Deposited: |
29 Nov 2018 17:58 |
Publisher: |
arXiv |
URI: |
|
Use Licence: |
This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available
here |
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