Measuring multivariate redundant information with pointwise common change in surprisal

Understand

The problem of how to properly quantify redundant information is an open question that has been the subject of much recent research.

• Redundant information refers to information about a target variable S that is common to two or more predictor variables Xi.
• It can be thought of as quantifying overlapping information content or similarities in the representation of S between the Xi.
• We present a new measure of redundancy which measures the common change in surprisal shared between variables at the local or pointwise level.