3 papers
cs.IT2019
Direct and Indirect Effects -- An Information Theoretic Perspective
Gabriel Schamberg, William Chapman, Shang-Ping Xie +1
Information theoretic (IT) approaches to quantifying causal influences have experienced some popularity in the literature, in both theoretical and applied (e.g. neuroscience and cl…
cs.IT2019
On the Bias of Directed Information Estimators
Gabriel Schamberg, Todd P. Coleman
When estimating the directed information between two jointly stationary Markov processes, it is typically assumed that the recipient of the directed information is itself Markov of…
cs.IT2018
A Sample Path Measure of Causal Influence
Gabriel Schamberg, Todd P. Coleman
We present a sample path dependent measure of causal influence between two time series. The proposed measure is a random variable whose expected sum is the directed information. A…