Algorithm 878: Exact VARMA likelihood and its gradient for complete and incomplete data with Matlab

Matlab functions for the evaluation of the exact log-likelihood of VAR and VARMA time series models are presented (vector autoregressive moving average). The functions accept incomplete data, and calculate analytical gradients, which may be used in parameter estimation with numerical likelihood maxi...

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Bibliographic Details
Published in:ACM transactions on mathematical software 2008-07, Vol.35 (1), p.1-11
Main Author: Jonasson, Kristjan
Format: Article
Language:English
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Summary:Matlab functions for the evaluation of the exact log-likelihood of VAR and VARMA time series models are presented (vector autoregressive moving average). The functions accept incomplete data, and calculate analytical gradients, which may be used in parameter estimation with numerical likelihood maximization. Allowance is made for possible savings when estimating seasonal, structured or distributed lag models. Also provided is a function for creating simulated VARMA time series that have an accurate distribution from term one (they are spin-up free). The functions are accompanied by a a simple example driver, a program demonstrating their use for real parameter fitting, as well as a test suite for verifying their correctness and aid further development. The article concludes with description of numerical results obtained with the algorithm.
ISSN:0098-3500
1557-7295
DOI:10.1145/1377603.1377609