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Construction of Multi-level space-filling designs via Code Mappings

Acta Mathematicae Applicatae Sinica 2022年第1期38卷 24-36页

作者： Hui-li XUE Xing-you HUANG Hong-yi LI College of Mathematics and Statistics Jishou UniversityJishou 416000China

space-filling designs are widely used in various fields because of their nice space-filling *** designs are one of space-filling designs,which desires the experimental points to scatter uniformly over the experimental *** practical need,the construction and their properties of nine-level uniform designs are discussed via two code mappings in this ***,the algorithm of constructing nine-level uniform designs is presented from an initial three-level design by the Type-I code mapping and tripling ***,the algorithm of constructing nine-level uniform designs is presented from a three-level base design by the Type-II code mapping and generalized orthogonal ***,relative properties are discussed based on the two code ***,some numerical examples are given out for supporting our theoretical results.

关键词： space-filling design uniformity wrap-around L2-discrepancy generalized minimum aberration code mapping

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On the maximin distance properties of orthogonal designs via the rotation

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Science China Mathematics 2023年第7期66卷 1593-1608页

作者： Yaping Wang Fasheng Sun Key Laboratory of Advanced Theory and Application in Statistics and Data Science Ministry of EducationSchool of StatisticsEast China Normal UniversityShanghai 200062China Key Laboratory for Applied Statistics of Ministry of Education School of Mathematics and StatisticsNortheast Normal UniversityChangchun 130024China

space-filling designs are widely used in computer *** are frequently evaluated by the orthogonality and distance-related *** orthogonal arrays is an appealing approach to constructing orthogonal space-filling *** important issue that has been rarely addressed in the literature is the design selection for the initial orthogonal *** paper studies the maximin L_(2)-distance properties of orthogonal designs generated by rotating two-level orthogonal arrays under three *** provide theoretical justifications for the rotation method from a maximin distance perspective and further propose to select initial orthogonal arrays by the minimum G_(2)-aberration *** infinite families of orthogonal or 3-orthogonal U-type designs,which also perform well under the maximin distance criterion,are obtained and *** are presented to show the effectiveness of the constructed designs for building statistical surrogate models.

关键词： computer experiment Latin hypercube design minimum G_(2)-aberration space-filling design U-type design

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A prediction-oriented optimal design for visualisation recommender systems

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Statistical Theory and Related Fields 2021年第2期5卷 134-148页

作者： Yingyan Zeng Xinwei Deng Xiaoyu Chen Ran Jin Grado Department of Industrial and Systems Engineering Virginia TechBlacksburgVAUSA Department of Statistics Virginia TechBlacksburgVAUSA

A good visualisation method can greatly enhance human-machine collaboration in target *** aid the optimal selection of visualisations for users,visualisation recommender systems have been developed to provide the right visualisation method to the right person given specific contexts.A visualisation recommender system often relies on a user study to collect data and conduct analysis to provide personalised ***,a user study without employing an effective experimental design is typically expensive in terms of time and *** this work,we propose a prediction-oriented optimal design to determine the user-task allocation in the user study for the recommendation of visualisation *** proposed optimal design will not only encourage the learning of the similarity embedded in the recommendation responses(i.e.,users’preference),but also improve the modelling accuracy of the similarities captured by the covariates of contexts(i.e.,task attributes).A simulation study and a real-data case study are used to evaluate the proposed optimal design.

关键词： design of experiments space-filling design user-task allocation V-optimality visualisation recommender system

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