System and method for testing prediction model

Details System and method for testing prediction model System and method for testing prediction model

1997-01-31

1999-04-06

MacDonald, Allen R.

Data processing: financial, business practice, management, or co

Automated electrical financial or business practice or...

705 7, 705 11, 702179, 702182, G06F 1760

Patent

active

058930698

ABSTRACT:
A computer-implemented prediction model evaluation method includes specifying many prediction models and a benchmark model against which the prediction models will be evaluated. A primary data matrix is arranged by data indices, and the primary matrix is sampled with replacement N times to bootstrap N observation matrices. Then, all the matrices are filled with measurement criteria, with each criteria being representative of a respective data index and a respective model. A p-value estimate is returned that measures the statistical significance of the best prediction model relative to the benchmark, where the p-value represents the probability of wrongly rejecting the null hypothesis that a best prediction model has expected performance no better than that of a benchmark. The p-value accounts for the examination of all of the prediction models, i.e., the p-value depends on the examination of all of the models as a group, and not simply on a single model.

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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