Numerically statistical investigation of the partly super-exponential growth rate in the COVID-19 pandemic (throughout the world)

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Numerically statistical investigation of the partly super-exponential growth rate in the COVID-19 pandemic (throughout the world). / Lotova, Galiya Z.; Mikhailov, Guennady A.

In: Journal of Inverse and Ill-Posed Problems, Vol. 28, No. 6, 01.12.2020, p. 877-879.

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

BibTeX

@article{7f1ead05b9ca4b5cb904bf871c55b697,

title = "Numerically statistical investigation of the partly super-exponential growth rate in the COVID-19 pandemic (throughout the world)",

abstract = "A number of particles in a multiplying medium under rather general conditions is asymptotically exponential with respect to time t with the parameter λ, i.e., with the index of power λt. If the medium is random, then the parameter λ is the random variable. To estimate the temporal asymptotics of the mean particles number (via the medium realizations), it is possible to average the exponential function via the corresponding distribution. Assuming that this distribution is Gaussian, the super-exponential estimate of the mean particle number could be obtained and expressed by the exponent with the index of power tEλ + t2Dλ/2. The application of this new formula to investigation of the COVID-19 pandemic is performed. ",

keywords = "COVID-19, statistical investigation, The novel Coronavirus pandemic",

author = "Lotova, {Galiya Z.} and Mikhailov, {Guennady A.}",

year = "2020",

month = dec,

day = "1",

doi = "10.1515/jiip-2020-0043",

language = "English",

volume = "28",

pages = "877--879",

journal = "Journal of Inverse and Ill-Posed Problems",

issn = "0928-0219",

publisher = "Walter de Gruyter GmbH",

number = "6",

}

RIS

TY - JOUR

T1 - Numerically statistical investigation of the partly super-exponential growth rate in the COVID-19 pandemic (throughout the world)

AU - Lotova, Galiya Z.

AU - Mikhailov, Guennady A.

PY - 2020/12/1

Y1 - 2020/12/1

N2 - A number of particles in a multiplying medium under rather general conditions is asymptotically exponential with respect to time t with the parameter λ, i.e., with the index of power λt. If the medium is random, then the parameter λ is the random variable. To estimate the temporal asymptotics of the mean particles number (via the medium realizations), it is possible to average the exponential function via the corresponding distribution. Assuming that this distribution is Gaussian, the super-exponential estimate of the mean particle number could be obtained and expressed by the exponent with the index of power tEλ + t2Dλ/2. The application of this new formula to investigation of the COVID-19 pandemic is performed.

AB - A number of particles in a multiplying medium under rather general conditions is asymptotically exponential with respect to time t with the parameter λ, i.e., with the index of power λt. If the medium is random, then the parameter λ is the random variable. To estimate the temporal asymptotics of the mean particles number (via the medium realizations), it is possible to average the exponential function via the corresponding distribution. Assuming that this distribution is Gaussian, the super-exponential estimate of the mean particle number could be obtained and expressed by the exponent with the index of power tEλ + t2Dλ/2. The application of this new formula to investigation of the COVID-19 pandemic is performed.

KW - COVID-19

KW - statistical investigation

KW - The novel Coronavirus pandemic

UR - http://www.scopus.com/inward/record.url?scp=85092407805&partnerID=8YFLogxK

U2 - 10.1515/jiip-2020-0043

DO - 10.1515/jiip-2020-0043

M3 - Article

AN - SCOPUS:85092407805

VL - 28

SP - 877

EP - 879

JO - Journal of Inverse and Ill-Posed Problems

JF - Journal of Inverse and Ill-Posed Problems

SN - 0928-0219

IS - 6

ER -

ID: 25677586