Parameter estimation for the stochastic SIS epidemic model

Alison Gray; Jiafeng Pan; David Greenhalgh; Xuerong Mao

Parameter estimation for the stochastic SIS epidemic model

Alison Gray, Jiafeng Pan, David Greenhalgh, Xuerong Mao

Mathematics And Statistics

Research output: Contribution to conference › Presentation/Speech

Abstract

In this work [1] we estimate the parameters in the stochastic SIS (susceptible-infected-susceptible) epidemic model [2] by using pseudo-maximum likelihood estimation (pseudo-MLE) and least squares estimation. We obtain the point estimators and 100(1−α)% confidence intervals as well as 100(1 − α)% joint confidence regions by applying least squares techniques. The pseudo-MLEs have almost the same form as the least squares case. We also obtain the exact as well as the asymptotic 100(1 − α)% joint confidence regions for the pseudo-MLEs. Computer simulations are used to illustrate our theory.

Original language	English
Publication status	Unpublished - Jun 2015
Event	26th Numerical Analysis Conference - University of Strathclyde, Glasgow, United Kingdom Duration: 23 Jun 2015 → 26 Jun 2015

Conference

Conference	26th Numerical Analysis Conference
Country/Territory	United Kingdom
City	Glasgow
Period	23/06/15 → 26/06/15

Keywords

susceptible-infected-susceptible model
stochastic SIS
parameter estimation

Cite this

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title = "Parameter estimation for the stochastic SIS epidemic model",

abstract = "In this work [1] we estimate the parameters in the stochastic SIS (susceptible-infected-susceptible) epidemic model [2] by using pseudo-maximum likelihood estimation (pseudo-MLE) and least squares estimation. We obtain the point estimators and 100(1−α)% confidence intervals as well as 100(1 − α)% joint confidence regions by applying least squares techniques. The pseudo-MLEs have almost the same form as the least squares case. We also obtain the exact as well as the asymptotic 100(1 − α)% joint confidence regions for the pseudo-MLEs. Computer simulations are used to illustrate our theory.",

keywords = "susceptible-infected-susceptible model, stochastic SIS, parameter estimation",

author = "Alison Gray and Jiafeng Pan and David Greenhalgh and Xuerong Mao",

year = "2015",

month = jun,

language = "English",

note = "26th Numerical Analysis Conference ; Conference date: 23-06-2015 Through 26-06-2015",

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TY - CONF

T1 - Parameter estimation for the stochastic SIS epidemic model

AU - Gray, Alison

AU - Pan, Jiafeng

AU - Greenhalgh, David

AU - Mao, Xuerong

PY - 2015/6

Y1 - 2015/6

N2 - In this work [1] we estimate the parameters in the stochastic SIS (susceptible-infected-susceptible) epidemic model [2] by using pseudo-maximum likelihood estimation (pseudo-MLE) and least squares estimation. We obtain the point estimators and 100(1−α)% confidence intervals as well as 100(1 − α)% joint confidence regions by applying least squares techniques. The pseudo-MLEs have almost the same form as the least squares case. We also obtain the exact as well as the asymptotic 100(1 − α)% joint confidence regions for the pseudo-MLEs. Computer simulations are used to illustrate our theory.

AB - In this work [1] we estimate the parameters in the stochastic SIS (susceptible-infected-susceptible) epidemic model [2] by using pseudo-maximum likelihood estimation (pseudo-MLE) and least squares estimation. We obtain the point estimators and 100(1−α)% confidence intervals as well as 100(1 − α)% joint confidence regions by applying least squares techniques. The pseudo-MLEs have almost the same form as the least squares case. We also obtain the exact as well as the asymptotic 100(1 − α)% joint confidence regions for the pseudo-MLEs. Computer simulations are used to illustrate our theory.

KW - susceptible-infected-susceptible model

KW - stochastic SIS

KW - parameter estimation

UR - http://numericalanalysisconference.org.uk/

M3 - Presentation/Speech

T2 - 26th Numerical Analysis Conference

Y2 - 23 June 2015 through 26 June 2015

ER -

Parameter estimation for the stochastic SIS epidemic model

Abstract

Conference

Keywords

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