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We consider the case of graded rather than binary measurements in Sect. 5.
Following the work developed for binary measurements, the problem of optimal input design with multiple sensor thresholds is tackled.
Other algorithms for curve matching use polygonal arc methods [47], matching the curve structure on the most significant scales [48], unary and binary measurements invariant for curves [49], fuzzy logic [50] or Sethian's Fast Marching method [51].
On the basis of a simple multiplicative risk model proposed elsewhere for repeated binary measurements, we derive the maximum likelihood estimator (MLE) for the proportion ratio (PR) of responses between two treatments in closed form without the need of modeling the complicated relationship between patient's compliance and patient's response.
We assessed the reliability of binary measurements with the κ statistic.
We included risk factors according to binary measurements (eg, yes vs no for having a first-degree relative with PD and ever versus never for alcohol).
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Our second main result, Theorem 2, applies this criterion to networks generated from a broad class of random graph ensembles with a randomly chosen binary measurement vector M. We show that the importance measures of individual edges cluster tightly around one of two values.
We have focused here on discrete state ion-channel models with binary measurement vectors.
The first development in this direction, for simple correlated binary measurement noise, was provided in [30].
Beta distribution is typically used to describe binary measurement system <α, β>.
In this paper, we formulate the construction of sparse binary measurement matrices from an optimization standpoint.
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