Standard

Goodness-of-Fit Tests Based on a Characterization of Logistic Distribution. / Nikitin, Ya.Yu.; Ragozin, I.A.

в: Vestnik St. Petersburg University: Mathematics, Том 52, № 2, 01.04.2019, стр. 169-177.

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

Harvard

Nikitin, YY & Ragozin, IA 2019, 'Goodness-of-Fit Tests Based on a Characterization of Logistic Distribution', Vestnik St. Petersburg University: Mathematics, Том. 52, № 2, стр. 169-177. https://doi.org/10.1134/S1063454119020122

APA

Nikitin, Y. Y., & Ragozin, I. A. (2019). Goodness-of-Fit Tests Based on a Characterization of Logistic Distribution. Vestnik St. Petersburg University: Mathematics, 52(2), 169-177. https://doi.org/10.1134/S1063454119020122

Vancouver

Nikitin YY, Ragozin IA. Goodness-of-Fit Tests Based on a Characterization of Logistic Distribution. Vestnik St. Petersburg University: Mathematics. 2019 Апр. 1;52(2):169-177. https://doi.org/10.1134/S1063454119020122

Author

Nikitin, Ya.Yu. ; Ragozin, I.A. / Goodness-of-Fit Tests Based on a Characterization of Logistic Distribution. в: Vestnik St. Petersburg University: Mathematics. 2019 ; Том 52, № 2. стр. 169-177.

BibTeX

@article{e988f9ff092d4f31b946122400390985,
title = "Goodness-of-Fit Tests Based on a Characterization of Logistic Distribution",
abstract = "The logistic family of distributions belongs to the class of important families in the theory of probability and mathematical statistics. However, the goodness-of-fit tests for the composite hypothesis of belonging to the logistic family with unknown location parameter against the general alternatives have not been sufficiently explored. We propose two new goodness-of-fit tests: the integral and the Kolmogorov-type, based on the recent characterization of the logistic family by Hua and Lin. Here we discuss asymptotic properties of new tests and calculate their Bahadur efficiency for common alternatives.",
keywords = "Kullback-Leibler information, asymptotic efficiency, characterization of distributions, large deviations, logistic distribution",
author = "Ya.Yu. Nikitin and I.A. Ragozin",
note = "Nikitin, Y.Y. & Ragozin, I.A. Vestnik St.Petersb. Univ.Math. (2019) 52: 169. https://doi.org/10.1134/S1063454119020122",
year = "2019",
month = apr,
day = "1",
doi = "10.1134/S1063454119020122",
language = "English",
volume = "52",
pages = "169--177",
journal = "Vestnik St. Petersburg University: Mathematics",
issn = "1063-4541",
publisher = "Pleiades Publishing",
number = "2",

}

RIS

TY - JOUR

T1 - Goodness-of-Fit Tests Based on a Characterization of Logistic Distribution

AU - Nikitin, Ya.Yu.

AU - Ragozin, I.A.

N1 - Nikitin, Y.Y. & Ragozin, I.A. Vestnik St.Petersb. Univ.Math. (2019) 52: 169. https://doi.org/10.1134/S1063454119020122

PY - 2019/4/1

Y1 - 2019/4/1

N2 - The logistic family of distributions belongs to the class of important families in the theory of probability and mathematical statistics. However, the goodness-of-fit tests for the composite hypothesis of belonging to the logistic family with unknown location parameter against the general alternatives have not been sufficiently explored. We propose two new goodness-of-fit tests: the integral and the Kolmogorov-type, based on the recent characterization of the logistic family by Hua and Lin. Here we discuss asymptotic properties of new tests and calculate their Bahadur efficiency for common alternatives.

AB - The logistic family of distributions belongs to the class of important families in the theory of probability and mathematical statistics. However, the goodness-of-fit tests for the composite hypothesis of belonging to the logistic family with unknown location parameter against the general alternatives have not been sufficiently explored. We propose two new goodness-of-fit tests: the integral and the Kolmogorov-type, based on the recent characterization of the logistic family by Hua and Lin. Here we discuss asymptotic properties of new tests and calculate their Bahadur efficiency for common alternatives.

KW - Kullback-Leibler information

KW - asymptotic efficiency

KW - characterization of distributions

KW - large deviations

KW - logistic distribution

UR - http://www.scopus.com/inward/record.url?scp=85067072521&partnerID=8YFLogxK

UR - https://link.springer.com/article/10.1134/S1063454119020122#enumeration

U2 - 10.1134/S1063454119020122

DO - 10.1134/S1063454119020122

M3 - Article

VL - 52

SP - 169

EP - 177

JO - Vestnik St. Petersburg University: Mathematics

JF - Vestnik St. Petersburg University: Mathematics

SN - 1063-4541

IS - 2

ER -

ID: 42190584