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The key idea is to use the criterion of DQ-optimality, which is a quadratic approximation of the criterion of D-optimality in the neighbourhood of the approximate D-optimal information matrix.
In addition, let us introduce the empirical approximation of the criterion (19) as {J}_kleft(s/widehat{mathbf{W}}right)=frac{1}{k}{displaystyle sum_{i=1}^kFleft(frac{eleft i,widehat{mathbf{W}}right)}{s}right)} (21).
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A first order method, also called a vertex direction method, uses a local linear approximation of the optimality criterion at the actual point.
Convex optimisation, based on a quadrature approximation of the IMSE criterion and a discretisation of the design space, yields an optimal design in the form of a probability measure with finite support.
Moreover, we propose an approximation of the mixed criteria which amounts to solving a single scalar nonlinear equation.
We selected the best of these features using the approach proposed by Peng et al. [16]; the method is an optimal first-order approximation of the mutual information criteria.
The classification scheme represents an approximation of the 2004 diagnostic criteria of the International Headache Society (IHS) 17 for migraine with or without aura, which were formalised after the Reykjavik Study data were collected.
An optimization problem is formulated considering the collision avoidance, the approximation of the given task curve and critical optimization criteria.
Models were compared using the Bayesian information criterion, which is an approximation of the marginal likelihood.
This criterion can be considered to be a good approximation of the 2D Delaunay if the point cloud is well-sampled and not too rough.
Instead, an approximation of the average rate is considered in this paper following the same criteria used in papers like [12, 27, 28].
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com