SYSTEM AND METHOD FOR ESTIMATING A PARAMETER THAT REPRESENTS DATA DESCRIBING A PHYSICAL SYSTEM

• US 20100274642A1
• Filed: 04/22/2009
• Published: 10/28/2010
• Est. Priority Date: 04/22/2009
• Status: Active Grant

• Current Assignee: Micro Focus LLC (Open Text Corporation)
• Original Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Inventors: Safai, Fereydoon, Shan, Jerry Z.
• Granted Patent: US 8,290,880 B2
• Time in Patent Office: Days
• US Class Current: 705/14.100
• CPC Class Codes: G06Q 30/0207 Discounts or incentives, e.g. coupons or rebates
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 40/02 Banking, e.g. interest calculation or account maintenance credit or loans G06Q40/03

Abstract

There is provided a system and method for estimating a parameter that represents data describing a physical system. An exemplary method comprises randomizing data representative of a population of items for which the parameter is known. The method may additionally comprise generating data representative of a pseudo population of items using a known perturbation, the data representative of the pseudo population of items being included with the data representative of the population of items for which the parameter is known to form a revised population and selecting a bootstrap sample of a minimum sample size of the revised population. A sensitivity study is performed on the parameters of the items comprising the bootstrap sample to determine a level of change of a predicted parameter value relative to a parameter value of the sample. At least one of a range, a probability distribution or the minimum sample size is revised based on the parameter for items comprising the bootstrap sample to produce at least one of a revised range, a revised probability distribution or a revised minimum sample size, taking into account an effect of the known perturbation applied to the pseudo population. The steps of selecting, performing and revising are repeated until the sensitivity study indicates that the level of change of the parameter is acceptably small. A value of the parameter is estimated for the population based on a parameter corresponding to the acceptably small level of change.

Claims

1. A computer-implemented method for estimating a parameter that represents data describing a physical system, the method comprising:

randomizing data representative of a population of items for which the parameter is known;

generating data representative of a pseudo population of items using a known perturbation, the data representative of the pseudo population of items being included with the data representative of the population of items for which the parameter is known to form a revised population;

selecting a bootstrap sample of a minimum sample size of the revised population;

performing a sensitivity study on the parameters of the items comprising the bootstrap sample to determine a level of change of a predicted parameter value relative to a parameter value of the bootstrap sample;

revising at least one of a range, a probability distribution or the minimum sample size of a model that predicts the parameter based on the level of change to produce at least one of a revised range, a revised probability distribution or a revised minimum sample size, taking into account an effect of the known perturbation applied to the pseudo population;

repeating the steps of selecting, performing and revising until the sensitivity study indicates that the level of change of the predicted parameter value is acceptably small; and

estimating a value of the parameter for the population based on the predicted parameter value that corresponds to the acceptably small level of change.

2. The method recited in claim 1, wherein the known perturbation comprises random noise.

3. The method recited in claim 1, wherein the physical system comprises a financial system.

4. The method recited in claim 1, wherein the physical system comprises a networked information technology system.

5. The method recited in claim 1, wherein the physical system comprises hardware elements and service elements.

6. The method recited in claim 1, wherein the parameter comprises a sales discount rate.

7. The method recited in claim 1, wherein the parameter corresponds to pricing consistency.

8. A computer-implemented method for estimating sales discounts, the method comprising:

randomizing a population of a plurality of transactions involving a physical system, each of the plurality of transactions having a discount rate associated therewith;

generating a pseudo population of transactions using a known perturbation, the pseudo population of transactions being included with the population of the plurality of transactions having discount rates to form a revised plurality of transactions;

selecting a sample of a minimum sample size of the revised plurality of transactions;

performing a sensitivity study on the discount rates of the transactions comprising the sample to determine a level of change of a predicted discount rate relative to the parameter values of the transactions comprising the sample;

revising at least one of a range, a probability distribution or the minimum sample size based on the level of change to produce at least one of a revised range, a revised probability distribution or a revised minimum sample size, taking into account an effect of the known perturbation of the pseudo population of transactions;

repeating the steps of selecting, performing and revising until the sensitivity study indicates that the level of change of the predicted discount rate is acceptably small; and

estimating a discount rate for the population of the plurality of transactions based on a discount rate corresponding to the acceptably small level of change.

9. The method recited in claim 8, wherein the known perturbation comprises random noise.

10. The method recited in claim 8, wherein the physical system comprises a financial system.

11. The method recited in claim 8, wherein the physical system comprises a networked information technology system.

12. The method recited in claim 8, wherein the physical system comprises hardware elements and service elements.

13. The method recited in claim 8, wherein the discount rate corresponds to a level of pricing consistency.

14. A computer system for estimating a parameter that represents data describing a physical system, the computer system comprising:

a processor that is adapted to execute stored instructions; and

a memory device that stores instructions that are executable by the processor, the instructions comprising;

computer-implemented instructions adapted to randomize data representative of a population of items for which the parameter is known;

computer-implemented instructions adapted to generate data representative of a pseudo population of items using a known perturbation, the data representative of the pseudo population of items being included with the data representative of the population of items for which the parameter is known to form a revised population;

computer-implemented instructions adapted to select a sample of a minimum sample size of the revised population;

computer-implemented instructions adapted to perform a sensitivity study on the parameters of the items comprising the sample to determine a level of change of a predicted parameter value relative to a parameter value of the sample;

computer-implemented instructions adapted to revise at least one of a range, a probability distribution or the minimum sample size of a model that predicts the parameter based on the level of change to produce at least one of a revised range, a revised probability distribution or a revised minimum sample size, taking into account an effect of the known perturbation applied to the pseudo population;

computer-implemented instructions adapted to repeat the steps of selecting, performing and revising until the sensitivity study indicates that the level of change of the predicted parameter value is acceptably small; and

computer-implemented instructions adapted to estimate a value of the parameter for the population based on the predicted parameter value that corresponds to the acceptably small level of change.

15. The computer system recited in claim 14, wherein the known perturbation comprises random noise.

16. The computer system recited in claim 14, wherein the physical system comprises a financial system.

17. The computer system recited in claim 14, wherein the physical system comprises a networked information technology system.

18. The computer system recited in claim 14, wherein the physical system comprises hardware elements and service elements.

19. The computer system recited in claim 14, wherein the parameter comprises a sales discount rate.

20. The computer system recited in claim 14, wherein the parameter corresponds to pricing consistency.