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Robust Designs for Discriminating between Trigonometric Regression Models. / Melas, V. B.; Shpilev, P. V.; Nikolaeva, O. Yu.

In: Vestnik St. Petersburg University: Mathematics, Vol. 52, No. 1, 2019, p. 66-74.

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Melas, VB, Shpilev, PV & Nikolaeva, OY 2019, 'Robust Designs for Discriminating between Trigonometric Regression Models', Vestnik St. Petersburg University: Mathematics, vol. 52, no. 1, pp. 66-74. https://doi.org/10.3103/S1063454119010096

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Melas, V. B. ; Shpilev, P. V. ; Nikolaeva, O. Yu. / Robust Designs for Discriminating between Trigonometric Regression Models. In: Vestnik St. Petersburg University: Mathematics. 2019 ; Vol. 52, No. 1. pp. 66-74.

BibTeX

@article{79e043061f2642848245dec43c4d9eaa,
title = "Robust Designs for Discriminating between Trigonometric Regression Models",
abstract = "This study is devoted to the issue of constructing robust T-optimal discriminating designs for two competing trigonometric regression models, which differ by three trigonometric functions at most. To solve this problem, we propose using a Bayesian and standardized maximin approaches. The robust T-optimal discriminating designs were found explicitly in a number of particular cases. In the general case, on account of the complexity of the optimization problem, the corresponding optimal designs are not easy to find and have to be determined numerically. The results are illustrated by means of several examples.",
keywords = "Bayesian designs, discriminating problems, robust T-optimal designs, standardized maximin designs, trigonometric regression models",
author = "Melas, {V. B.} and Shpilev, {P. V.} and Nikolaeva, {O. Yu}",
note = "Melas, V.B., Shpilev, P.V. & Nikolaeva, O.Y. Vestnik St.Petersb. Univ.Math. (2019) 52: 66. https://doi.org/10.3103/S1063454119010096",
year = "2019",
doi = "10.3103/S1063454119010096",
language = "English",
volume = "52",
pages = "66--74",
journal = "Vestnik St. Petersburg University: Mathematics",
issn = "1063-4541",
publisher = "Pleiades Publishing",
number = "1",

}

RIS

TY - JOUR

T1 - Robust Designs for Discriminating between Trigonometric Regression Models

AU - Melas, V. B.

AU - Shpilev, P. V.

AU - Nikolaeva, O. Yu

N1 - Melas, V.B., Shpilev, P.V. & Nikolaeva, O.Y. Vestnik St.Petersb. Univ.Math. (2019) 52: 66. https://doi.org/10.3103/S1063454119010096

PY - 2019

Y1 - 2019

N2 - This study is devoted to the issue of constructing robust T-optimal discriminating designs for two competing trigonometric regression models, which differ by three trigonometric functions at most. To solve this problem, we propose using a Bayesian and standardized maximin approaches. The robust T-optimal discriminating designs were found explicitly in a number of particular cases. In the general case, on account of the complexity of the optimization problem, the corresponding optimal designs are not easy to find and have to be determined numerically. The results are illustrated by means of several examples.

AB - This study is devoted to the issue of constructing robust T-optimal discriminating designs for two competing trigonometric regression models, which differ by three trigonometric functions at most. To solve this problem, we propose using a Bayesian and standardized maximin approaches. The robust T-optimal discriminating designs were found explicitly in a number of particular cases. In the general case, on account of the complexity of the optimization problem, the corresponding optimal designs are not easy to find and have to be determined numerically. The results are illustrated by means of several examples.

KW - Bayesian designs

KW - discriminating problems

KW - robust T-optimal designs

KW - standardized maximin designs

KW - trigonometric regression models

UR - http://www.scopus.com/inward/record.url?scp=85064907753&partnerID=8YFLogxK

U2 - 10.3103/S1063454119010096

DO - 10.3103/S1063454119010096

M3 - Article

AN - SCOPUS:85064907753

VL - 52

SP - 66

EP - 74

JO - Vestnik St. Petersburg University: Mathematics

JF - Vestnik St. Petersburg University: Mathematics

SN - 1063-4541

IS - 1

ER -

ID: 42871965