Enciso-Mora, Victor and Neal, Peter and Subba Rao, Tata (2006) Efficient order selection algorithms for integer valued ARMA processes. [MIMS Preprint]
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Abstract
We consider the problem of model (order) selection for integer valued autoregressive moving-average (INARMA) processes. A very efficient Reversible Jump Markov chain Monte Carlo (RJMCMC) algorithm is constructed for moving between INARMA processes of different order. An alternative in the form of the EM algorithm is given for determining the order of an integer valued autoregressive (INAR) process. Both algorithms are successfully applied to both simulated and real data sets.
Item Type: | MIMS Preprint |
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Additional Information: | Submitted to Journal of Time Series Analysis |
Uncontrolled Keywords: | Integer valued time-series, Reversible jump MCMC, EM algorithm, count data |
Subjects: | MSC 2010, the AMS's Mathematics Subject Classification > 62 Statistics |
Depositing User: | Dr Peter Neal |
Date Deposited: | 12 Dec 2006 |
Last Modified: | 08 Nov 2017 18:18 |
URI: | https://eprints.maths.manchester.ac.uk/id/eprint/665 |
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