Results 31 to 40 of about 12,796 (278)
Fast Computation of Highly G-optimal Exact Designs via Particle Swarm Optimization
, 2022 Computing proposed exact $G$-optimal designs for response surface models is a difficult computation that has received incremental improvements via algorithm development in the last two-decades. These optimal designs have not been considered widely in applications in part due to the difficulty and cost involved with computing them.
Walsh, Stephen J., Borkowski, John J.
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Design of Calibration Experiments for Identification of Manipulator Elastostatic Parameters [PDF]
, 2012 The paper is devoted to the elastostatic calibration of industrial robots, which is used for precise machining of large-dimensional parts made of composite materials.
Caro, Stéphane +4 more
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Comparing robust properties of A, D, E and G-optimal designs [PDF]
Computational Statistics & Data Analysis, 1994 We examine the A, D, E and G-efficiencies of using the optimal design for the polynomial regression model of degree k when the hypothesized model is of degree j and 1 Q j < k Q 8. The robustness properties of each of these optimal designs with respect to the other optimal&y criteria are also investigated.
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CaTchDes: MATLAB codes for Caratheodory–Tchakaloff Near-Optimal Regression Designs
SoftwareX, 2019 We provide a MATLAB package for the computation of near-optimal sampling sets and weights (designs) for nth degree polynomial regression on discretizations of planar, surface and solid domains.
Len Bos, Marco Vianello
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Constructing model robust mixture designs via weighted G-optimality criterion
International Journal of Industrial Engineering Computations, 2019 Proponemos y desarrollamos un nuevo criterio de optimalidad G utilizando el concepto de criterios de optimalidad ponderados y ciertas generalizaciones adicionales. El objetivo de la optimalidad G ponderada es minimizar un promedio ponderado de la varianza máxima de predicción escalada en la región de diseño sobre un conjunto de modelos reducidos.
Wanida Limmun +2 more
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Optimality Conditions and Duality for DC Programming in Locally Convex Spaces
Journal of Inequalities and Applications, 2009 Consider the DC programming problem (PA) infx∈X{f(x)−g(Ax)}, where f and g are proper convex functions defined on locally convex Hausdorff topological vector spaces X and Y, respectively, and A is a linear operator from X to Y.
Xianyun Wang
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A Note on $G$- Optimal Stopping Problems
, 2012 This paper has been withdrawn by the authors due to some crucial error in some ...
Guo, Xin, Pan, Chen, Peng, Shige
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G‐optimal grid designs for kriging models
Scandinavian Journal of StatisticsAbstractThis work is focused on finding G‐optimal designs theoretically for kriging models with two‐dimensional inputs and separable exponential covariance structures. For design comparison, the notion of evenness of two‐dimensional grid designs is developed.
Subhadra Dasgupta +2 more
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New Optimality Conditions for a Nondifferentiable Fractional Semipreinvex Programming Problem
Journal of Applied Mathematics, 2013 We study a nondifferentiable fractional programming problem as follows: (P)minx∈Kf(x)/g(x) subject to x∈K⊆X, hi(x)≤0, i=1,2,…,m, where K is a semiconnected subset in a locally convex topological vector space X, f:K→ℝ, g:K→ℝ+ and hi:K→ℝ, i=1,2,…, m. If
Yi-Chou Chen, Wei-Shih Du
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Effects of missing observations on predictive capability of central composite designs
, 2014 Quite often in experimental work, many situations arise where some observations are lost or become unavailable due to some accidents or cost constraints.
Adebayo, Bamiduro Timothy +3 more
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