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On assignment problem for heavy tailed random variables. / Лифшиц, Михаил Анатольевич; Shi, Zhan.

In: Sankhya: The Indian Journal of Statistics, 13.06.2025.

Research output: Contribution to journal › Article › peer-review

Harvard

Лифшиц, МА & Shi, Z 2025, 'On assignment problem for heavy tailed random variables', Sankhya: The Indian Journal of Statistics. https://doi.org/10.1007/s13171-025-00396-8

APA

Лифшиц, М. А., & Shi, Z. (2025). On assignment problem for heavy tailed random variables. Sankhya: The Indian Journal of Statistics. https://doi.org/10.1007/s13171-025-00396-8

Vancouver

Лифшиц МА, Shi Z. On assignment problem for heavy tailed random variables. Sankhya: The Indian Journal of Statistics. 2025 Jun 13. https://doi.org/10.1007/s13171-025-00396-8

Author

Лифшиц, Михаил Анатольевич ; Shi, Zhan. / On assignment problem for heavy tailed random variables. In: Sankhya: The Indian Journal of Statistics. 2025.

BibTeX

@article{b5c1734b6cb64890973a3f6598c58035,
title = "On assignment problem for heavy tailed random variables",
abstract = "We consider the asymptotic behavior of the maximum for assignment process with heavy tailed independent and identically distributed entries. We prove a limit theorem on convergence to the unilateral stable law for the case when the expectation of entries is infinite while for the case of finite expectation of entries we provide upper and lower bounds of the same order for maximum{\textquoteright}s expectation.",
keywords = "процесс назначений, Expectation estimates, Heavy tails, Limit theorem, Random assignment",
author = "Лифшиц, {Михаил Анатольевич} and Zhan Shi",
year = "2025",
month = jun,
day = "13",
doi = "10.1007/s13171-025-00396-8",
language = "English",
journal = "Sankhya: The Indian Journal of Statistics",
issn = "0972-7671",
publisher = "Indian Statistical Institute",

}

RIS

TY - JOUR

T1 - On assignment problem for heavy tailed random variables

AU - Лифшиц, Михаил Анатольевич

AU - Shi, Zhan

PY - 2025/6/13

Y1 - 2025/6/13

N2 - We consider the asymptotic behavior of the maximum for assignment process with heavy tailed independent and identically distributed entries. We prove a limit theorem on convergence to the unilateral stable law for the case when the expectation of entries is infinite while for the case of finite expectation of entries we provide upper and lower bounds of the same order for maximum’s expectation.

AB - We consider the asymptotic behavior of the maximum for assignment process with heavy tailed independent and identically distributed entries. We prove a limit theorem on convergence to the unilateral stable law for the case when the expectation of entries is infinite while for the case of finite expectation of entries we provide upper and lower bounds of the same order for maximum’s expectation.

KW - процесс назначений

KW - Expectation estimates

KW - Heavy tails

KW - Limit theorem

KW - Random assignment

UR - https://www.mendeley.com/catalogue/405ff378-5a5e-38b6-8c76-696770e52560/

U2 - 10.1007/s13171-025-00396-8

DO - 10.1007/s13171-025-00396-8

M3 - Article

JO - Sankhya: The Indian Journal of Statistics

JF - Sankhya: The Indian Journal of Statistics

SN - 0972-7671

ER -

ID: 142794440