tsdata_to_autocov_debias (EXPERIMENTAL)
Calculate sample autocovariance sequence from time series data with debias
Syntax
G = tsdata_to_autocov_debias(X,q)
Arguments
See also Common variable names and data structures.
input
X multi-trial time series data q number of lags
output
G sample autocovariance sequence
Description
Returns q-lag sample autocovariance sequence G defined as 
for the (presumed stationary) multivariate process X. X may contain single- or multi-trial time series data. See tsdata_to_autocov for more details.
This (experimental) algorithm [2] attempts to reduce bias due to mean estimation for small samples.
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 ].
[2] Y. Shkolnisky, F. J. Sigworth and A. Singer, A note on estimating autocovariance from short-time observations, 2008.