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Model selection for time series of count data
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Alzahrani, Naif, Neal, Peter, Spencer, Simon E. F., McKinley, Trevelyan J. and Touloupou, Panayiota (2018) Model selection for time series of count data. Computational Statistics & Data Analysis, 122 . pp. 33-44. doi:10.1016/j.csda.2018.01.002 ISSN 0167-9473.
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Official URL: https://doi.org/10.1016/j.csda.2018.01.002
Abstract
Selecting between competing statistical models is a challenging problem especially when the competing models are non-nested. An effective algorithm is developed in a Bayesian framework for selecting between a parameter-driven autoregressive Poisson regression model and an observation-driven integer valued autoregressive model when modelling time series count data. In order to achieve this a particle MCMC algorithm for the autoregressive Poisson regression model is introduced. The particle filter underpinning the particle MCMC algorithm plays a key role in estimating the marginal likelihood of the autoregressive Poisson regression model via importance sampling and is also utilised to estimate the DIC. The performance of the model selection algorithms are assessed via a simulation study. Two real-life data sets, monthly US polio cases (1970–1983) and monthly benefit claims from the logging industry to the British Columbia Workers Compensation Board (1985–1994) are successfully analysed.
Item Type: | Journal Article | ||||||
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Subjects: | Q Science > QA Mathematics | ||||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||||
Library of Congress Subject Headings (LCSH): | Regression analysis., Time-series analysis., Linear models (Statistics), Mathematical statistics -- Data processing., Correlation (Statistics) | ||||||
Journal or Publication Title: | Computational Statistics & Data Analysis | ||||||
Publisher: | Elsevier Science Ltd | ||||||
ISSN: | 0167-9473 | ||||||
Official Date: | 11 January 2018 | ||||||
Dates: |
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Volume: | 122 | ||||||
Page Range: | pp. 33-44 | ||||||
DOI: | 10.1016/j.csda.2018.01.002 | ||||||
Status: | Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||
Date of first compliant deposit: | 4 January 2018 | ||||||
Date of first compliant Open Access: | 26 February 2018 | ||||||
RIOXX Funder/Project Grant: |
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