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pro vyhledávání: '"Wolverton A"'
We construct an optimal exponential tail decreasing confidence region for an unknown density of distribution in the Lebesgue-Riesz as well as in the uniform} norm, built on the sample of the random vectors based of the famous recursive Wolverton-Wagn
Externí odkaz:
http://arxiv.org/abs/2409.01451
We derive the exponential non improvable Grand Lebesgue Space norm decreasing estimations for tail of distribution for exact normed deviation for the famous recursive Wolverton-Wagner multivariate statistical density estimation. We consider pointwise
Externí odkaz:
http://arxiv.org/abs/2102.07867
Autor:
Comte, Fabienne, Marie, Nicolas
Publikováno v:
Journal of Statistical Planning and Inference 207, 198-214, 2020
For $n$ independent random variables having the same H\"older continuous density, this paper deals with controls of the Wolverton-Wagner's estimator MSE and MISE. Then, for a bandwidth $h_n(\beta)$, estimators of $\beta$ are obtained by a Goldenshlug
Externí odkaz:
http://arxiv.org/abs/1902.00734
Autor:
Martin, Paul S., Szuter, Christine R.
Publikováno v:
Conservation Biology, 2002 Feb 01. 16(1), 244-247.
Externí odkaz:
https://www.jstor.org/stable/3061418
Searching for technologically promising crystalline materials with desired thermal transport properties requires an electronic level comprehension of interatomic interactions and chemical intuition to uncover the hidden structure-property relationshi
Externí odkaz:
http://arxiv.org/abs/2410.16066
Akademický článek
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Autor:
Bales, Roger C. rbales@ucmerced.edu, Stacy, Erin M., Meng, Xiande, Conklin, Martha H., Kirchner, Peter B., Zheng, Zeshi
Publikováno v:
Earth System Science Data. 2018, Vol. 10 Issue 4, p2115-2122. 8p. 1 Chart, 4 Graphs, 1 Map.
Autor:
Cooney, Barbara Leigh
Publikováno v:
International Journal on World Peace, 2020 Dec 01. 37(4), 94-98.
Externí odkaz:
https://www.jstor.org/stable/27115998
Phonons play a critical role in determining various material properties, but conventional methods for phonon calculations are computationally intensive, limiting their broad applicability. In this study, we present an approach to accelerate high-thro
Externí odkaz:
http://arxiv.org/abs/2407.09674