What scientific folklore knows about the distances between the most popular distributions

M. Y. Kelbert; Yu M. Suhov

doi:10.18500/1816-9791-2022-22-2-233-240

What scientific folklore knows about the distances between the most popular distributions

M. Y. Kelbert, Yu M. Suhov

Mathematics

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

Abstract

We present a number of upper and low bounds for the total variation distances between the most popular probability distributions. In particular, some estimates of the total variation distances between one-dimensional Gaussian distributions, between two Poisson distributions, between two binomial distributions, between a binomial and a Poisson distribution, and also between two negative binomial distributions are given. The Kolmogorov - Smirnov distance is also presented.

Original language	English (US)
Pages (from-to)	233-240
Number of pages	8
Journal	Izvestiya of Saratov University. New Series. Series: Mathematics. Mechanics. Informatics
Volume	22
Issue number	2
DOIs	https://doi.org/10.18500/1816-9791-2022-22-2-233-240
State	Published - 2022

All Science Journal Classification (ASJC) codes

General Computer Science
Computational Mechanics
General Mathematics
Mechanics of Materials
Mechanical Engineering

Access to Document

10.18500/1816-9791-2022-22-2-233-240

Cite this

@article{a73c47bca7af48b382af5a14172a84b2,

title = "What scientific folklore knows about the distances between the most popular distributions",

abstract = "We present a number of upper and low bounds for the total variation distances between the most popular probability distributions. In particular, some estimates of the total variation distances between one-dimensional Gaussian distributions, between two Poisson distributions, between two binomial distributions, between a binomial and a Poisson distribution, and also between two negative binomial distributions are given. The Kolmogorov - Smirnov distance is also presented.",

author = "Kelbert, {M. Y.} and Suhov, {Yu M.}",

year = "2022",

doi = "10.18500/1816-9791-2022-22-2-233-240",

language = "English (US)",

volume = "22",

pages = "233--240",

journal = "Izvestiya of Saratov University. New Series. Series: Mathematics. Mechanics. Informatics",

issn = "1816-9791",

publisher = "Saratov National Research State University",

number = "2",

}

TY - JOUR

T1 - What scientific folklore knows about the distances between the most popular distributions

AU - Kelbert, M. Y.

AU - Suhov, Yu M.

PY - 2022

Y1 - 2022

N2 - We present a number of upper and low bounds for the total variation distances between the most popular probability distributions. In particular, some estimates of the total variation distances between one-dimensional Gaussian distributions, between two Poisson distributions, between two binomial distributions, between a binomial and a Poisson distribution, and also between two negative binomial distributions are given. The Kolmogorov - Smirnov distance is also presented.

AB - We present a number of upper and low bounds for the total variation distances between the most popular probability distributions. In particular, some estimates of the total variation distances between one-dimensional Gaussian distributions, between two Poisson distributions, between two binomial distributions, between a binomial and a Poisson distribution, and also between two negative binomial distributions are given. The Kolmogorov - Smirnov distance is also presented.

UR - http://www.scopus.com/inward/record.url?scp=85132720175&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85132720175&partnerID=8YFLogxK

U2 - 10.18500/1816-9791-2022-22-2-233-240

DO - 10.18500/1816-9791-2022-22-2-233-240

M3 - Article

AN - SCOPUS:85132720175

SN - 1816-9791

VL - 22

SP - 233

EP - 240

JO - Izvestiya of Saratov University. New Series. Series: Mathematics. Mechanics. Informatics

JF - Izvestiya of Saratov University. New Series. Series: Mathematics. Mechanics. Informatics

IS - 2

ER -

What scientific folklore knows about the distances between the most popular distributions

Abstract

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this