Data processing: measuring – calibrating – or testing – Measurement system – Measured signal processing
Reexamination Certificate
2008-01-29
2008-01-29
Cosimano, Edward (Department: 2863)
Data processing: measuring, calibrating, or testing
Measurement system
Measured signal processing
C702S179000, C702S181000
Reexamination Certificate
active
11416680
ABSTRACT:
The present invention is directed to a method for information analysis used to discriminate between biased and unbiased fits. A goodness-of-fit parameter becomes a quantity of interest for analysis of multiple measurements and does so by replacing a likelihood function with a probability of the likelihood function W(L|α). The probability of the likelihood function is derived from a new posterior probability P(α|L) and the goodness-of-fit parameter G, wherein a is a set of fitting parameters, L is the likelihood function and W(L|α) is equal to the product of P(α|L) and G. Furthermore, if substantial prior information is available on α, then the probability of the fitting parameters P(α) can is used to aid in the determination of W(L|α).
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Maximal information analysis: I-various Wayne state plots and the most common likelihood principle; G. Bonvicini, Physics Department, Wayne State University; Jun. 14, 2005.
Cosimano Edward
Gifford Krass Sprinkle Anderson & Citkowski P.C.
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