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190802 ||| eng |
| 020 |
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|a 9789811380754
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| 100 |
1 |
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|a Sawa, Masanori
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| 245 |
0 |
0 |
|a Euclidean Design Theory
|h Elektronische Ressource
|c by Masanori Sawa, Masatake Hirao, Sanpei Kageyama
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| 250 |
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|a 1st ed. 2019
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| 260 |
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|a Singapore
|b Springer Nature Singapore
|c 2019, 2019
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| 300 |
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|a VIII, 134 p. 14 illus., 12 illus. in color
|b online resource
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| 505 |
0 |
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|a Chapter I: Reproducing Kernel Hilbert Space -- Chapter II: Cubature Formula -- Chapter III: Optimal Euclidean Design -- Chapter IV: Constructions of Optimal Euclidean Design -- Chapter V: Euclidean Design Theory
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| 653 |
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|a Statistical Theory and Methods
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| 653 |
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|a Statistics
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| 653 |
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|a Statistics in Business, Management, Economics, Finance, Insurance
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| 653 |
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|a Mathematical statistics—Data processing
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| 653 |
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|a Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences
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| 653 |
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|a Statistics and Computing
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| 700 |
1 |
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|a Hirao, Masatake
|e [author]
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| 700 |
1 |
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|a Kageyama, Sanpei
|e [author]
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 490 |
0 |
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|a JSS Research Series in Statistics
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| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-981-13-8075-4?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 519.5
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| 520 |
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|a This book is the modern first treatment of experimental designs, providing a comprehensive introduction to the interrelationship between the theory of optimal designs and the theory of cubature formulas in numerical analysis. It also offers original new ideas for constructing optimal designs. The book opens with some basics on reproducing kernels, and builds up to more advanced topics, including bounds for the number of cubature formula points, equivalence theorems for statistical optimalities, and the Sobolev Theorem for the cubature formula. It concludes with a functional analytic generalization of the above classical results. Although it is intended for readers who are interested in recent advances in the construction theory of optimal experimental designs, the book is also useful for researchers seeking rich interactions between optimal experimental designs and various mathematical subjects such as spherical designs in combinatorics and cubature formulas in numerical analysis, both closely related to embeddings of classical finite-dimensional Banach spaces in functional analysis and Hilbert identities in elementary number theory. Moreover, it provides a novel communication platform for “design theorists” in a wide variety of research fields
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