Patent ID: 8543523

Claim:
A method in a computing system for calibrating a subject data set based on information from a reference data set, each data set containing a plurality of participants and associated transactional data, the method comprising: using a data partitioning scheme, partitioning the reference data set into a plurality of reference data partitions, each of the plurality of reference data partitions having an associated transactional characteristic and no two reference data partitions sharing a participant in common; using the data partitioning scheme, partitioning the subject data set into a plurality of subject data partitions, wherein: each of the plurality of subject data partitions has an associated transactional characteristic that is the same as the transactional characteristic associated with the corresponding reference data partition or has a high degree of correspondence with the transactional characteristic associated with the corresponding reference data partition; and no two subject data partitions of the plurality of subject data partitions share a participant in common; calculating weights associated with each of the plurality of subject data partitions to adjust for subject data partitions that are under- or over-represented, the weights calculated to adjust a distribution of the plurality of subject data partitions to be the same as a distribution of the plurality of reference data set partitions; calculating a statistic for each of the plurality of subject data partitions; and adjusting, by the computing system, the calculated statistics by applying the calculated weight for each subject data partition to the calculated statistic for each subject data partition, the applied weights producing calibrated estimates of the statistics for the plurality of subject data partitions.