Data processing: structural design – modeling – simulation – and em – Modeling by mathematical expression
Reexamination Certificate
2003-06-17
2009-08-25
Phan, Thai (Department: 2128)
Data processing: structural design, modeling, simulation, and em
Modeling by mathematical expression
C700S031000, C700S083000, C706S058000
Reexamination Certificate
active
07580813
ABSTRACT:
The present invention utilizes a cross-prediction scheme to predict values of discrete and continuous time observation data, wherein conditional variance of each continuous time tube variable is fixed to a small positive value. By allowing cross-predictions in an ARMA based model, values of continuous and discrete observations in a time series are accurately predicted. The present invention accomplishes this by extending an ARMA model such that a first time series “tube” is utilized to facilitate or “cross-predict” values in a second time series tube to form an “ARMAxp” model. In general, in the ARMAxp model, the distribution of each continuous variable is a decision graph having splits only on discrete variables and having linear regressions with continuous regressors at all leaves, and the distribution of each discrete variable is a decision graph having splits only on discrete variables and having additional distributions at all leaves.
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Chickering David M.
Heckerman David E.
Meek Christopher A.
Thiesson Bo
Lee & Hayes PLLC
Microsoft Corporation
Phan Thai
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