The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Oct. 06, 2020

Filed:

Aug. 14, 2018
Applicant:

Triad National Security, Llc, Los Alamos, NM (US);

Inventors:

Nicolas Hengartner, Los Alamos, NM (US);

Leticia Cuellar-Hengartner, Los Alamos, NM (US);

Assignee:

Triad National Security, LLC, Los Alamos, NM (US);

Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06Q 30/00 (2012.01); G06Q 10/06 (2012.01); G06Q 40/06 (2012.01); G06N 7/00 (2006.01); G06F 17/16 (2006.01); G06F 17/18 (2006.01); G06F 17/15 (2006.01);
U.S. Cl.
CPC ...
G06Q 10/0635 (2013.01); G06F 17/15 (2013.01); G06F 17/16 (2013.01); G06F 17/18 (2013.01); G06N 7/00 (2013.01); G06Q 10/067 (2013.01); G06Q 40/06 (2013.01);
Abstract

Effects in multiple linear regression may be decorrelated to decompose and attribute risk to common and proper effects. In other words, an attribute risk may be decomposed to two or more causes, where each cause is characterized by multiple attributes. The risk decomposition may decompose risk into a first residual part associated with a first set of risk factors, a second residual part associated with a second set of risk factors, and a common part associated with a set of common hidden variables that minimize a correlation between the first set of factors and the second set of factors. The common hidden variables may be modeled using a hidden factor model. An effect of the correlation may be minimized on the first set of risk factors and the second set of risk factors, and how correlated the terms of the risk decomposition are may be quantified.


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