FT_CONNECTIVITY_DTF
Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_connectivity_dtf”.
FT_CONNECTIVITY_DTF computes the directed transfer function. Use as [d, v, n] = ft_connectivity_dtf(h, ...) The input data h should be a spectral transfer matrix organized as Nrpt x Nchan x Nchan x Nfreq (x Ntime), where Nrpt can be 1. Additional optional input arguments come as key-value pairs: 'hasjack' = 0 (default) is a boolean specifying whether the input contains leave-one-outs, required for correct variance estimate. 'feedback' = string, determining verbosity (default = 'none'), see FT_PROGRESS 'crsspctrm' = matrix containing the cross-spectral density. If this matrix is defined, the function returns the ddtf, which requires an estimation of partial coherence from this matrix. 'invfun' = 'inv' (default) or 'pinv', the function used to invert the crsspctrm matrix to obtain the partial coherence. Pinv is useful if the data are poorly-conditioned. Output arguments: d = partial directed coherence matrix Nchan x Nchan x Nfreq (x Ntime). If multiple observations in the input, the average is returned. v = variance of d across observations. n = number of observations. Typically, nrpt should be 1 (where the spectral transfer matrix is computed across observations. When nrpt>1 and hasjack is true the input is assumed to contain the leave-one-out estimates of H, thus a more reliable estimate of the relevant quantities. See also FT_CONNECTIVITYANALYSIS