This toolbox implements routines based on univariate (spm_ar) and multivariate autoregressive modelling (spm_mar), including time and frequency domain Granger causality analysis, coherence and power spectral analysis. The routines allow you to estimate the optimal number of time lags in the AR/MAR models. There is also a routine for robust autoregressive modelling (spm_rar) in which the error process is a twocomponent mixture model (to run this routine you will need the mixture toolbox on your search path). There is no user interface but there are many demo files.

W.D. Penny and S.J. Roberts. Bayesian Multivariate Autoregresive Models with structured priors. IEE Proceedings on Vision, Image and Signal Processing, 149(1):33-41, 2002
 
These descriptions of the new features are taken from the SPM8 Release Notes
 
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