Efficient order selection algorithms for integer valued ARMA processes

Enciso-Mora, Victor and Neal, Peter and Subba Rao, Tata (2006) Efficient order selection algorithms for integer valued ARMA processes. [MIMS Preprint]

[thumbnail of model_051206.pdf] PDF

Download (187kB)


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
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

Actions (login required)

View Item View Item