mvgc_cval

Critical values for sample MVGC based on theoretical asymptotic null distribution

Syntax

   x = mvgc_cval(alpha,p,m,N,nx,ny,nz,tstat)

Arguments

See also Common variable names and data structures.

input

   alpha      vector of significance levels
   p          VAR model order
   m          number of observations per trial
   N          number of trials
   nx         number of target ("to") variables
   ny         number of source ("from") variables
   nz         number of conditioning variables (default: 0)
   tstat      statistic: 'F' or 'chi2' (default: 'F' if nx == 1, else 'chi2')

output

   x          vector of critical MVGC values

Description

Returns critical MVGC values x at significance levels in alpha for sample MVGC, based on theoretical (asymptotic) null distribution. See mvgc_cdfi for details of other parameters.

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 ].

See also

mvgc_cdf | mvgc_cdfi | mvgc_pval | mvgc_confint | mvgc_demo_confint | mvgc_demo_nonstationary

MVGC Toolbox v1.0. © Lionel Barnett and Anil K. Seth, 2012.
See file license.txt for licensing terms.