Extinction and Quasi-Stationarity in the Stochastic Logistic SIS Model

This volume presents explicit approximations of the quasi-stationary distribution and of the expected time to extinction from the state one and from quasi-stationarity for the stochastic logistic SIS model. The approximations are derived separately in three different parameter regions, and then comb...

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Κύριος συγγραφέας: Nåsell, Ingemar (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2011.
Σειρά:Lecture Notes in Mathematics, 2022
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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245 1 0 |a Extinction and Quasi-Stationarity in the Stochastic Logistic SIS Model  |h [electronic resource] /  |c by Ingemar Nåsell. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg :  |b Imprint: Springer,  |c 2011. 
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490 1 |a Lecture Notes in Mathematics,  |x 0075-8434 ;  |v 2022 
505 0 |a 1 Introduction -- 2 Model Formulation -- 3 A Birth-Death Process with Finite State Space and with an Absorbing State at the Origin -- 4 The SIS Model: First Approximations of the Quasi-Stationary Distribution -- 5 Some Approximations Involving the Normal Distribution -- 6 Preparations for the Study of the Stationary Distribution p(1) of the SIS Model -- 7 Approximation of the Stationary Distribution p(1) of the SIS Model -- 8 Preparations for the Study of the Stationary Distribution p(0) of the SIS Model -- 9 Approximation of the Stationary Distribution p(0) of the SIS Model -- 10 Approximation of Some Images UnderY for the SIS Model -- 11 Approximation of the Quasi-Stationary Distribution q of the SIS Model -- 12 Approximation of the Time to Extinction for the SIS Model -- 13 Uniform Approximations for the SIS Model -- 14 Thresholds for the SIS Model -- 15 Concluding Comments. 
520 |a This volume presents explicit approximations of the quasi-stationary distribution and of the expected time to extinction from the state one and from quasi-stationarity for the stochastic logistic SIS model. The approximations are derived separately in three different parameter regions, and then combined into a uniform approximation across all three regions. Subsequently, the results are used to derive thresholds as functions of the population size N. 
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650 0 |a Life sciences. 
650 0 |a Probabilities. 
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650 2 4 |a Probability Theory and Stochastic Processes. 
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776 0 8 |i Printed edition:  |z 9783642205293 
830 0 |a Lecture Notes in Mathematics,  |x 0075-8434 ;  |v 2022 
856 4 0 |u http://dx.doi.org/10.1007/978-3-642-20530-9  |z Full Text via HEAL-Link 
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