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Efficient computation of Bayesian optimal discriminating designs. / Dette, Holger; Guchenko, Roman; Melas, Viatcheslav B.

в: Journal of Computational and Graphical Statistics, Том 26, № 2, 2017, стр. 424-433.

Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование

Harvard

Dette, H, Guchenko, R & Melas, VB 2017, 'Efficient computation of Bayesian optimal discriminating designs', Journal of Computational and Graphical Statistics, Том. 26, № 2, стр. 424-433. https://doi.org/10.1080/10618600.2016.1195272

APA

Dette, H., Guchenko, R., & Melas, V. B. (2017). Efficient computation of Bayesian optimal discriminating designs. Journal of Computational and Graphical Statistics, 26(2), 424-433. https://doi.org/10.1080/10618600.2016.1195272

Vancouver

Dette H, Guchenko R, Melas VB. Efficient computation of Bayesian optimal discriminating designs. Journal of Computational and Graphical Statistics. 2017;26(2):424-433. https://doi.org/10.1080/10618600.2016.1195272

Author

Dette, Holger ; Guchenko, Roman ; Melas, Viatcheslav B. / Efficient computation of Bayesian optimal discriminating designs. в: Journal of Computational and Graphical Statistics. 2017 ; Том 26, № 2. стр. 424-433.

BibTeX

@article{79b9a75f59224be1b96c2c7518ee9206,
title = "Efficient computation of Bayesian optimal discriminating designs",
author = "Holger Dette and Roman Guchenko and Melas, {Viatcheslav B.}",
year = "2017",
doi = "10.1080/10618600.2016.1195272",
language = "English",
volume = "26",
pages = "424--433",
journal = "Journal of Computational and Graphical Statistics",
issn = "1061-8600",
publisher = "Taylor & Francis",
number = "2",

}

RIS

TY - JOUR

T1 - Efficient computation of Bayesian optimal discriminating designs

AU - Dette, Holger

AU - Guchenko, Roman

AU - Melas, Viatcheslav B.

PY - 2017

Y1 - 2017

U2 - 10.1080/10618600.2016.1195272

DO - 10.1080/10618600.2016.1195272

M3 - Article

VL - 26

SP - 424

EP - 433

JO - Journal of Computational and Graphical Statistics

JF - Journal of Computational and Graphical Statistics

SN - 1061-8600

IS - 2

ER -

ID: 7611071