On the sub-Gaussianity of the missing mass

Yanpeng Li; Boping Tian

doi:10.1016/j.spl.2023.109991

On the sub-Gaussianity of the missing mass

Yanpeng Li^*
, Boping Tian

^*Corresponding author for this work

School of Mathematics, Harbin Institute of Technology

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

Abstract

We sharpen the best-known sub-Gaussian concentration of the missing mass to the variance factor c/n for some 0<c<1/2 in terms of the alphabet size under multinomial sampling. A simple lower bound for c is also demonstrated.

Original language	English
Article number	109991
Journal	Statistics and Probability Letters
Volume	206
DOIs	https://doi.org/10.1016/j.spl.2023.109991
State	Published - Mar 2024
Externally published	Yes

Keywords

Missing mass
Multinomial sampling
Sub-Gaussian

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10.1016/j.spl.2023.109991

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title = "On the sub-Gaussianity of the missing mass",

abstract = "We sharpen the best-known sub-Gaussian concentration of the missing mass to the variance factor c/n for some 0",

keywords = "Missing mass, Multinomial sampling, Sub-Gaussian",

author = "Yanpeng Li and Boping Tian",

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year = "2024",

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doi = "10.1016/j.spl.2023.109991",

language = "英语",

volume = "206",

journal = "Statistics and Probability Letters",

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AU - Li, Yanpeng

AU - Tian, Boping

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AB - We sharpen the best-known sub-Gaussian concentration of the missing mass to the variance factor c/n for some 0

KW - Missing mass

KW - Multinomial sampling

KW - Sub-Gaussian

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DO - 10.1016/j.spl.2023.109991

M3 - 文章

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SN - 0167-7152

VL - 206

JO - Statistics and Probability Letters

JF - Statistics and Probability Letters

M1 - 109991

ER -

On the sub-Gaussianity of the missing mass

Abstract

Keywords

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