System and method for testing prediction models and/or entities

Data processing: financial – business practice – management – or co – Automated electrical financial or business practice or...

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705 7, 705 10, G06F 1760

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active

060886765

ABSTRACT:
A computer-implemented performance evaluation method includes specifying a group of comparable entities and a benchmark against which the comparable entities are evaluated. The entities evaluated may be a process, technology, strategy, treatment, organization, individual, or other identifiable unit. A primary data matrix is arranged by data indices, and the primary matrix is sampled with replacement N times to bootstrap N observation matrices. Alternatively, a Monte Carlo approach can be used. Then, all the matrices are filled with measurement criteria, with each criterion being representative of a respective data index and a respective entity. A p-value estimate is returned that measures the statistical significance of the best of the comparable entities relative to the benchmark, where the p-value represents the probability of wrongly rejecting the null hypothesis that a best of the comparable entities has expected performance no better than that of a benchmark. The p-value accounts for the examination of all of the comparable entities, i.e., the p-value depends on the examination of all of the entities as a group, and not simply on a single entity.

REFERENCES:
patent: 5578923 (1996-11-01), Chen
patent: 5614718 (1997-03-01), Brace
patent: 5729465 (1998-03-01), Barbaresco
patent: 5732358 (1998-03-01), Sawaya et al.
patent: 5774829 (1998-06-01), Cisneros et al.
Article: The Stationary Bootstrap. Politis and Romano. Journal of the American Statistical Association. vol. 89, No. 428, Theory and Methods, Dec. 1994.

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