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Goodness-of-fit tests for logistic family via characterization. / Nikitin, Yakov; Rogozin, Ilya.

Book of Abstracts of the 18 th Applied Stochastic Models and Data Analysis International Conference with the Demographics 2019 Workshop. ed. / Christos H Skiadas. ISAST, 2019. p. 135.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Harvard

Nikitin, Y & Rogozin, I 2019, Goodness-of-fit tests for logistic family via characterization. in CH Skiadas (ed.), Book of Abstracts of the 18 th Applied Stochastic Models and Data Analysis International Conference with the Demographics 2019 Workshop. ISAST, pp. 135, 18th Applied Stochastic Models and Data Analysis International Conference with Demographics Workshop (ASMDA2019), Флоренция, Italy, 11/06/19.

APA

Nikitin, Y., & Rogozin, I. (2019). Goodness-of-fit tests for logistic family via characterization. In C. H. Skiadas (Ed.), Book of Abstracts of the 18 th Applied Stochastic Models and Data Analysis International Conference with the Demographics 2019 Workshop (pp. 135). ISAST.

Vancouver

Nikitin Y, Rogozin I. Goodness-of-fit tests for logistic family via characterization. In Skiadas CH, editor, Book of Abstracts of the 18 th Applied Stochastic Models and Data Analysis International Conference with the Demographics 2019 Workshop. ISAST. 2019. p. 135

Author

Nikitin, Yakov ; Rogozin, Ilya. / Goodness-of-fit tests for logistic family via characterization. Book of Abstracts of the 18 th Applied Stochastic Models and Data Analysis International Conference with the Demographics 2019 Workshop. editor / Christos H Skiadas. ISAST, 2019. pp. 135

BibTeX

@inproceedings{a29bbd6249da4758b2cc373ad8a58512,
title = "Goodness-of-fit tests for logistic family via characterization",
abstract = "The logistic family of distributions belongs to the class of important familiesin Probability and Statistics. However, the goodness-of-fit tests for the composite hypothesis on belonging to the logistic family with unknown location parameter against the general alternatives are almost unexplored. We propose two new goodness-of-fit tests, the integral and the Kolmogorov type, based on the recent characterization of logistic family due to Hu and Lin. They are build using the U-empirical measures. We discuss asymptotic properties of new tests such as their limiting distributions and large deviations, and calculate their local Bahadur efficiency against natural alternatives. Conditions of local asymptoticoptimality of new tests are also explored.",
author = "Yakov Nikitin and Ilya Rogozin",
note = "Book of Abstracts of 18th Applied Stochastic Models and Data Analysis International Conference with Demographics Workshop (ASMDA2019), зю135; null ; Conference date: 11-06-2019 Through 14-06-2019",
year = "2019",
month = may,
day = "4",
language = "English",
pages = "135",
editor = "Skiadas, {Christos H }",
booktitle = "Book of Abstracts of the 18 th Applied Stochastic Models and Data Analysis International Conference with the Demographics 2019 Workshop",
publisher = "ISAST",
address = "Greece",
url = "http://www.asmda.es",

}

RIS

TY - GEN

T1 - Goodness-of-fit tests for logistic family via characterization

AU - Nikitin, Yakov

AU - Rogozin, Ilya

N1 - Conference code: 18

PY - 2019/5/4

Y1 - 2019/5/4

N2 - The logistic family of distributions belongs to the class of important familiesin Probability and Statistics. However, the goodness-of-fit tests for the composite hypothesis on belonging to the logistic family with unknown location parameter against the general alternatives are almost unexplored. We propose two new goodness-of-fit tests, the integral and the Kolmogorov type, based on the recent characterization of logistic family due to Hu and Lin. They are build using the U-empirical measures. We discuss asymptotic properties of new tests such as their limiting distributions and large deviations, and calculate their local Bahadur efficiency against natural alternatives. Conditions of local asymptoticoptimality of new tests are also explored.

AB - The logistic family of distributions belongs to the class of important familiesin Probability and Statistics. However, the goodness-of-fit tests for the composite hypothesis on belonging to the logistic family with unknown location parameter against the general alternatives are almost unexplored. We propose two new goodness-of-fit tests, the integral and the Kolmogorov type, based on the recent characterization of logistic family due to Hu and Lin. They are build using the U-empirical measures. We discuss asymptotic properties of new tests such as their limiting distributions and large deviations, and calculate their local Bahadur efficiency against natural alternatives. Conditions of local asymptoticoptimality of new tests are also explored.

UR - http://www.asmda.es/images/Book_of_Abstracts_ASMDA2019-Demographics2019.pdf

M3 - Conference contribution

SP - 135

BT - Book of Abstracts of the 18 th Applied Stochastic Models and Data Analysis International Conference with the Demographics 2019 Workshop

A2 - Skiadas, Christos H

PB - ISAST

Y2 - 11 June 2019 through 14 June 2019

ER -

ID: 46402451