Asymptotic analysis of the SIR model. Applications to COVID-19 modelling

The SIR (Susceptible-Infected-Removed) model can be very useful in modelling epidemic outbreaks. The present paper derives the parametric solution of the model in terms of quadratures. The paper demonstrates a simple analytical asymptotic solution for the I-variable, which is valid on the entire real line. Moreover, the solution can be used successfully for parametric estimation either in stand-alone mode or as a preliminary step in the parametric estimation using numerical inversion of the parametric solution. The approach is applied to the ongoing coronavirus disease 2019 (COVID-19) pandemic in three European countries --Belgium, Italy and Sweden.

A Complete Asymptotic Expansion for Bernstein–Chlodovsky Polynomials for Functions on $$\mathbb {R}$$

We consider a variant of the Bernstein–Chlodovsky polynomials approximating continuous functions on the entire real line and study its rate of convergence. The main result is a complete asymptotic expansion. As a special case we obtain a Voronovskaja-type formula previously derived by Karsli [11].

Hybrid Clayton-Frank Convolution-Based Bivariate Archimedean Copula

This study exploits the closure property of the converse convolution operator to come up with a hybrid Clayton-Frank Archimedean copula for two random variables. Pairs of random variables were generated and the upper tail observation of the cumulative distribution function (CDF) was used to assess the right skew behavior of the proposed model. Various values of the converse convolution operator were used to see their effect on the proposed model. The simulation covered lengths n=10i, i=2,3,4,5, and 6. The proposed model was compared with about 40 other bivariate copulas (both Archimedean and elliptical). The proposed model had parameters that spanned the entire real line, thus removing restrictions on the parameters. The parameters theta and omega were varied for a selected interval and the hybrid Clayton-Frank model was, in most cases, found to outperform the other copulas under consideration.

On the Distribution of the Nearly Unstable AR(1) Process with Heavy Tails

We consider a nearly unstable, or near unit root, AR(1) process with regularly varying innovations. Two different approximations for the stationary distribution of such processes exist: a Gaussian approximation arising from the nearly unstable nature of the process and a heavy-tail approximation related to the tail asymptotics of the innovations. We combine these two approximations to obtain a new uniform approximation that is valid on the entire real line. As a corollary, we obtain a precise description of the regions where each of the Gaussian and heavy-tail approximations should be used.

On the Distribution of the Nearly Unstable AR(1) Process with Heavy Tails

We consider a nearly unstable, or near unit root, AR(1) process with regularly varying innovations. Two different approximations for the stationary distribution of such processes exist: a Gaussian approximation arising from the nearly unstable nature of the process and a heavy-tail approximation related to the tail asymptotics of the innovations. We combine these two approximations to obtain a new uniform approximation that is valid on the entire real line. As a corollary, we obtain a precise description of the regions where each of the Gaussian and heavy-tail approximations should be used.

On the control of a truncated general immigration process through the introduction of a predator

This paper is concerned with the problem of controlling a truncated general immigration process, which represents a population of harmful individuals, by the introduction of a predator. If the parameters of the model satisfy some mild conditions, the existence of a control-limit policy that is average-cost optimal is proved. The proof is based on the uniformization technique and on the variation of a fictitious parameter over the entire real line. Furthermore, an efficient Markov decision algorithm is developed that generates a sequence of improving control-limit policies converging to the optimal policy.

OPTIMAL CONTROL OF A SIMPLE IMMIGRATION PROCESS THROUGH THE INTRODUCTION OF A PREDATOR

This article is concerned with the problem of controlling a simple immigration process, which represents a pest population, by the introduction of a predator. It is assumed that the cost rate caused by the pests is an increasing function of their population size and that the cost rate of the controlling action is constant. The existence of a control-limit policy that minimizes the expected long-run average cost per unit time is established. The proof is based on the variation of a fictitious parameter over the entire real line.

Flows equivalences

<p>Given a differential equation on an open set O of an n-manifold we can associate to it a pseudo-flow, that is, a flow whose trajectories may not be defined in the entire real line. In this paper we prove that this pseudo-flow is always equivalent to a flow with its trajectories defined in all R. This result extends a similar result of Vinograd stated in the n-dimensional Euclidean space.</p>