RELATIONSHIP ANALYSIS DEVICE, RELATIONSHIP ANALYSIS METHOD, AND RECORDING MEDIUM
A relationship analysis device includes a parameter sample data calculation unit that calculates a plurality of pieces of sample data for parameters for a simulator that receives inputs of data of a first type and outputs data of a second type, calculating the plurality of pieces of sample data; a second type sample data acquisition unit that inputs, to the simulator, observation data of the first type and a plurality of pieces of sample data, and obtains sample data of the second type for each of the plurality of pieces of sample data; and a parameter value determination unit that calculates a weight for each of the plurality of pieces of sample data based on the difference between observation data of the second type and the calculated sample data of the second type and calculates a value for the parameters using the calculated weight.
1 . A relationship analysis device comprising:
at least one memory configured to store instructions; and
at least one processor configured to execute the instructions to:
calculate a plurality of pieces of sample data for parameters for a simulator, based on a temporarily set distribution for the parameters, the simulator receiving inputs of data of a first type and outputting data of a second type;
input, to the simulator, observation data of the first type and each of the plurality of pieces of sample data for the parameters, and obtain a sample data of the second type for each of the plurality of pieces of sample data for the parameters; and
calculate a weight for each of the plurality of pieces of sample data for the parameters based on the difference between observation data of the second type and the calculated sample data of the second type, and calculate a value for the parameters using the calculated weight.
2 . The relationship analysis device according to claim 1 , wherein the at least one processor is configured to execute the instructions to:
calculate a kernel mean indicating a posterior distribution of the parameters under the observation data of the first type and the calculated sample data of the second type;
calculate sample data of the parameters based on the kernel mean;
calculate a kernel expression of the predictive distribution of the parameters using sample data of the parameters based on the kernel mean; and
calculate sample data according to the predictive distribution of the data of the second type by using the kernel expression of the predictive distribution of the parameters.
3 . A relationship analysis method comprising:
calculating a plurality of pieces of sample data for parameters for a simulator that receives inputs of data of a first type and outputs data of a second type, calculating the of pieces of sample data based on a temporarily set distribution for the parameters;
inputting, to the simulator, observation data of the first type and each of a plurality of pieces of sample data for the parameters, and calculating sample data of the second type for each of the plurality of pieces of sample data for the parameters;
calculating a weight for each of the plurality of pieces of sample data for the parameters based on the difference between observation data of the second type and the calculated sample data of the second type; and
calculating a value for the parameters using the calculated weight.
4 . A non-transitory recording medium that records a program for causing a computer to execute:
calculating a plurality of pieces of sample data for parameters for a simulator that receives inputs of data of a first type and outputs data of a second type, calculating the plurality of pieces of sample data based on a temporarily set distribution for the parameters;
inputting, to the simulator, observation data of the first type and each of a plurality of pieces of sample data for the parameters, and calculating sample data of the second type for each of the plurality of pieces of sample data for the parameters;
calculating a weight for each of the plurality of pieces of sample data for the parameters based on the difference between observation data of the second type and the calculated sample data of the second type; and
calculating a value for the parameters using the calculated weight.