var_to_tsdata_nonstat
Generate random multi-trial non-stationary Gaussian VAR time series
Syntax
X = var_to_tsdata_nonstat(A,SIG,N)
Arguments
See also Common variable names and data structures.
input
A time-varying VAR coefficients matrix SIG time-varying residuals covariance matrix N number of trials (default: 1)
output
X multi-trial Gaussian VAR time series E residuals time series mtrunc number of initial time steps truncated
Description
Return N independent random Gaussian non-stationary VAR time series, with time-varying coefficients A and residuals covariances SIG. The last index in A and SIG is the time index (the number of observations is taken as the size of the last dimension). If SIG is 2 dimensional, then it is replicated at each time.
Useful for generating test data; see mvgc_demo_nonstationary.
References
[1] L. Barnett and A. K. Seth, The MVGC Multivariate Granger Causality Toolbox: A New Approach to Granger-causal Inference, J. Neurosci. Methods 223, 2014 [ preprint ].