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Titlebook: Euclidean Design Theory; Masanori Sawa,Masatake Hirao,Sanpei Kageyama Book 2019 The Author(s), under exclusive license to Springer Nature

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11#
發(fā)表于 2025-3-23 11:26:20 | 只看該作者
SpringerBriefs in CybersecurityThe present chapter provides a brief summary of basic ideas and facts concerning ., which are closely related to the theories of cubature formula being a certain class of integration formulas in numerical analysis, as well as of Euclidean design which is a special point configuration in the Euclidean space.
12#
發(fā)表于 2025-3-23 16:54:01 | 只看該作者
Property, Corporate, and Government Crime,A . reveals a numerical integration rule that approximates a multiple integral by a positive linear combination of function values at finitely many specified points on the integral domain. A central objective is to investigate the existence as well as the construction of cubature formulas in high dimensions.
13#
發(fā)表于 2025-3-23 19:58:20 | 只看該作者
14#
發(fā)表于 2025-3-24 02:11:10 | 只看該作者
Cubature Formula,A . reveals a numerical integration rule that approximates a multiple integral by a positive linear combination of function values at finitely many specified points on the integral domain. A central objective is to investigate the existence as well as the construction of cubature formulas in high dimensions.
15#
發(fā)表于 2025-3-24 06:12:01 | 只看該作者
estimated” with some statistical criterion. . is a popular criterion that seeks for designs minimizing the determinant of the covariance matrix. Here and hereafter, we are mainly concerned with .-optimal designs on the unit ball.
16#
發(fā)表于 2025-3-24 07:06:27 | 只看該作者
Kyle J. D. Mulrooney,Katinka van de Venent equations . for all monomials of degree up?to 2.. But a serious concern for this approach is that the number of equations rapidly grows with the number of unknown parameters . even in the quadratic or cubic regression?(.) in Sect.?3.1.
17#
發(fā)表于 2025-3-24 10:58:48 | 只看該作者
18#
發(fā)表于 2025-3-24 15:45:44 | 只看該作者
19#
發(fā)表于 2025-3-24 20:02:30 | 只看該作者
estimated” with some statistical criterion. . is a popular criterion that seeks for designs minimizing the determinant of the covariance matrix. Here and hereafter, we are mainly concerned with .-optimal designs on the unit ball.
20#
發(fā)表于 2025-3-24 23:25:11 | 只看該作者
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