Causal relationship inference device, causal relationship inference method, and storage record medium storing causal relationship inference program

A causal relationship inference device comprising:

• processing circuitry
• to read out a causal relationship parameter, indicating a causal relationship between time-series data of a plurality of state variables and time-series data of a plurality of observation variables in regard to each layer, from a causal relationship parameter database and to rearrange the time-series data of the plurality of state variables and the time-series data of the plurality of observation variables in regard to each layer based on the causal relationship parameter;
• to acquire verification data including a set of time-series data of a plurality of state variables and a set of time-series data of a plurality of observation variables;
• and
• to perform one or both of verification of Granger causality by use of the verification data and verification of a spurious correlation by use of the verification data on the rearranged time-series data of the plurality of state variables and the rearranged time-series data of the plurality of observation variables.

A causal relationship inference method to be executed by a causal relationship inference device, the method comprising:

• acquiring learning data including a set of time-series data of a plurality of state variables and a set of time-series data of a plurality of observation variables;
• calculating a causal relationship parameter indicating a causal relationship between the time-series data of the plurality of state variables and the time-series data of the plurality of observation variables, calculating a variance-covariance matrix of a Gaussian process from the learning data and the causal relationship parameter, and representing the causal relationship parameter by a multi-task Gaussian process model;
• and
• calculating an optimization function based on the variance-covariance matrix and updating the causal relationship parameter based on the optimization function.

A non-transitory computer-readable record medium storing a causal relationship inference program that causes a computer to execute:

• acquiring learning data including a set of time-series data of a plurality of state variables and a set of time-series data of a plurality of observation variables;
• calculating a causal relationship parameter indicating a causal relationship between the time-series data of the plurality of state variables and the time-series data of the plurality of observation variables, calculating a variance-covariance matrix of a Gaussian process from the learning data and the causal relationship parameter, and representing the causal relationship parameter by a multi-task Gaussian process model;
• and
• calculating an optimization function based on the variance-covariance matrix and updating the causal relationship parameter based on the optimization function.