Modelling correlated zero-inflated count data
Modelling correlated zero-inflated count data
This paper extends the two-component approach to modelling count data with extra zeros, considered by Mullahy (1986), Heilbron (1994) and Welsh et al. (1996), to take account of possible serial dependence between repeated observations. Generalized estimating equations (Liang & Zeger, 1986) are constructed for each component of the model by incorporating correlation matrices into each of the maximum likelihood estimating equations. The proposed method is demonstrated on weekly counts of Noisy Friarbirds (Philemon cornic-ulatus), which were recorded by observers for the Canberra Garden Bird Survey (Hermes, 1981)
431-444
Dobbie, Melissa J.
be258ed9-9605-490d-ba1b-69b747c26a08
Welsh, A.H.
27640871-afff-4d45-a191-8a72abee4c1a
2001
Dobbie, Melissa J.
be258ed9-9605-490d-ba1b-69b747c26a08
Welsh, A.H.
27640871-afff-4d45-a191-8a72abee4c1a
Dobbie, Melissa J. and Welsh, A.H.
(2001)
Modelling correlated zero-inflated count data.
Australian & New Zealand Journal of Statistics, 43 (4), .
(doi:10.1111/1467-842X.00191).
Abstract
This paper extends the two-component approach to modelling count data with extra zeros, considered by Mullahy (1986), Heilbron (1994) and Welsh et al. (1996), to take account of possible serial dependence between repeated observations. Generalized estimating equations (Liang & Zeger, 1986) are constructed for each component of the model by incorporating correlation matrices into each of the maximum likelihood estimating equations. The proposed method is demonstrated on weekly counts of Noisy Friarbirds (Philemon cornic-ulatus), which were recorded by observers for the Canberra Garden Bird Survey (Hermes, 1981)
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Published date: 2001
Organisations:
Statistics
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Local EPrints ID: 29937
URI: http://eprints.soton.ac.uk/id/eprint/29937
ISSN: 1369-1473
PURE UUID: f97150a8-9d15-45a7-9118-5fc484d02936
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Date deposited: 11 May 2006
Last modified: 15 Mar 2024 07:36
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Author:
Melissa J. Dobbie
Author:
A.H. Welsh
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