Whitlock, Mark E. and Queen, Catriona M.
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Whitlock and Queen (1998) developed a dynamic graphical model for forecasting traffic flows at a number of sites at a busy traffic junction in Kent, UK. Some of the data collection sites at this junction have been faulty over the data collection period and so there are missing series in the multivariate problem. Here we adapt the model developed in Whitlock and Queen (1998) to accommodate these missing data. Markov chain Monte Carlo methods are used to provide forecasts of the missing series, which in turn are used to produce forecasts for some of the other series. The methods are used on part of the network and shown to be very promising.
|Item Type:||Journal Article|
|Copyright Holders:||2000 John Wiley & Sons, Ltd|
|Keywords:||forecasting traffic networks; Bayesian dynamic graphical model; missing data; Markov chain Monte Carlo|
|Academic Unit/Department:||Faculty of Science, Technology, Engineering and Mathematics (STEM) > Mathematics and Statistics
Faculty of Science, Technology, Engineering and Mathematics (STEM)
|Depositing User:||Sarah Frain|
|Date Deposited:||06 Apr 2011 14:59|
|Last Modified:||04 Oct 2016 10:46|
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