How does multicollinearity affect brain connectivity estimation? A simulation study based on penalized regression technique
Methods based on the use of multivariate autoregressive modelling (MVAR) have proved to be an accurate and flexible tool for the estimation of brain connectivity. However, the multivariate approach, implies that the number of parameters to be estimated, increases quadratically with the number of time series included in the model. This can often lead to an undetermined problem and to the condition known as multicollinearity.