On the exceedance point process for a stationary sequence

Summary It is known that the exceedance points of a high level by a stationary sequence are asymptotically Poisson as the level increases, under appropriate long range and local dependence conditions. When the local dependence conditions are relaxed, clustering of exceedances may occur, based on Poisson positions for the clusters. In this paper a detailed analysis of the exceedance point process is given, and shows that, under wide conditions, any limiting point process for exceedances is necessarily compound Poisson. More generally the possible random measure limits for normalized exceedance point processes are characterized. Sufficient conditions are also given for the existence of a point process limit. The limiting distributions of extreme order statistics are derived as corollaries.This research has been supported by the Air Force Office of Scientific Research Grant No. F 49620 85 C 0144 and the Katholieke Universiteit Leuven     

A model of the direct interaction of elements of a tightly coupled system

A maximin mathematical model describing the process of changing the quality indicators of products manufactured by facilities of a complex production system interconnected by multiple feedbacks is considered. Necessary and sufficient conditions for the monotone growth of these indicators are found. For the proposed new technologies utilized on some of these facilities, consistency conditions with the technologies used on other facilities are determined. For finding the optimal control of this process, it is recommended to use parallel computations.     

Multiscale analysis and simulation of a reaction–diffusion problem with transmission conditions

This paper considers a transmission problem for partial differential equations obtained in the recent paper [M. Neuss-Radu, W. Jäger, Effective transmission conditions for reaction-diffusion processes in domains separated by an interface, SIAM J. Math. Anal. 39 (2007) 687–720] as the effective system modeling a reaction–diffusion process in two domains separated by a membrane. For the analysis of this problem an appropriate function space, which includes the coupling conditions for the concentrations on the interface, is introduced. The transmission conditions for the flux are included in the variational formulation with respect to this function space.The solution of the transmission problem is approximated by using the Galerkin method. Numerically the problem is reduced to a system of ordinary differential equations, where the coupling of the micro- and macro-variables leads to a special structure, distinguishing the variables relevant for the transmission. Results of numerical simulations are illustrating the effect of the microscopic process in the membrane on the macroscopic reaction–diffusion process in the bulk domains.     

The age of a Markov process

The concept of a limiting conditional age distribution of a continuous time Markov process whose state space is the set of non-negative integers and for which {0} is absorbing is defined as the weak limit as t→∞ of the last time before t an associated “return” Markov process exited from {0} conditional on the state, j, of this process at t. It is shown that this limit exists and is non-defective if the return process is ρ-recurrent and satisfies the strong ratio limit property. As a preliminary to the proof of the main results some general results are established on the representation of the ρ-invariant measure and function of a Markov process. The conditions of the main results are shown to be satisfied by the return process constructed from a Markov branching process and by birth and death processes. Finally, a number of limit theorems for the limiting age as j→∞ are given.     

Group theoretic approach for solving the problem of diffusion of a drug through a thin membrane

The transformation group theoretic approach is applied to study the diffusion process of a drug through a skin-like membrane which tends to partially absorb the drug. Two cases are considered for the diffusion coefficient. The application of one parameter group reduces the number of independent variables by one, and consequently the partial differential equation governing the diffusion process with the boundary and initial conditions is transformed into an ordinary differential equation with the corresponding conditions. The obtained differential equation is solved numerically using the shooting method, and the results are illustrated graphically and in tables.     

On a Markov process generated by non-decreasing concave functions

A discrete-time Markov process on [0, ∞) is considered. The process is generated by selecting at each time, in an independent and stationary way, a concave non-decreasing function. Sufficient conditions for the existence of a unique stationary limiting distribution are given.     

Structural identifiability of a model of dialysis

In this paper, structural identifiability from input–output data is considered. A mathematical model to describe a dialysis process based on linear dynamic systems is used and the identifiability of this model is tested. The problem of estimating the parameters and obtaining conditions to assure the uniqueness of the parameters is solved. Some conditions to obtain attractive points for the considered model are given, and finally, the stability problem is analyzed.     

On an inverse problem of reconstructing a subdiffusion process from nonlocal data

We consider a problem of modeling the thermal diffusion process in a closed metal wire wrapped around a thin sheet of insulation material. The layer of insulation is assumed to be slightly permeable. Therefore, the temperature value from one side affects the diffusion process on the other side. For this reason, the standard heat equation is modified, and a third term with an involution is added. Modeling of this process leads to the consideration of an inverse problem for a one‐dimensional fractional evolution equation with involution and with periodic boundary conditions with respect to a space variable. This equation interpolates heat equation. Such equations are also called nonlocal subdiffusion equations or nonlocal heat equations. The inverse problem consists in the restoration (simultaneously with the solution) of the unknown right‐hand side of the equation, which depends only on the spatial variable. The conditions for overdefinition are initial and final states. Existence and uniqueness results for the given problem are obtained via the method of separation of variables.     

The stability of a non-homogeneous queueing system with regenerative input

A queueing system with nonidentical service channels, a regenerative input, and a renewal service process at each channel is considered. The ergodic conditions are found when the basic process describing the system (and including the queue-size and the waiting time vector) is regenerative with finite expectation of the regeneration cycle length. The asymptotic properties of the embedded renewal process of the regeneration points are used. The zero-delayed and delayed cases are considered separately. Some queueing network applications are discussed. Supported by the Nordic Council of Ministers. Proceedings of the XVII Seminar on Stability Problems for Stochastic Models, Kazan, Russia, 1995, Part II.     

Monitoring a class of discrete point processes

A discrete, non-negative integer-valued, stationary point process was proposed by Neuts and Pearce as a model for teletraffic packet streams. We examine a data-analytic approach to develop a monitoring scheme for that point process. Monitoring is a procedure of tracking a stochastic process to identity quickly the development of anomalous situations in the evolution of the point process and to detect the assignable causes to account for such conditions. Numerical results are presented to illustrate the performance of the monitoring scheme.     

Hamiltonian systems with a stochastic force:nonlinear versus linear,and a girsanov formula

We discuss stochastic perturbations of classical Hamiltonian systems by a white noise force. We prove existence and uniqueness results for the solutions of the equation of motion under general conditions on the classical system, as well as their continuous dependence on the initial conditions. We also prove that the process in phase space is a diffusion with transition probability densities, and Lebesgue measure as c-finite invariant measure. We prove a Girsanov formula relating the solution for a nonlinear force with the one for a linear force, and give asymptotic estimates on functions of the phase space process     

Stochastic Differential Games With a Small Parameter

Much of stochastic game theory is concerned with diffusion models. Such models are often only idealizations of the actual physical process, which might be driven by a wide bandwidth process or be a discrete parameter system with correlated driving noises. For a two person zero-sum game, under quite general conditions, the optimal or nearly optimal strategies derived for the diffusion model are shown to be “nearly optimal” for the physical (say wideband noise driven) process. An approach based on occupation measures are used. We treat the problem of discounted cost, as well as the average cost per unit time problem. Weak convergence methods are utilized in the analysis     

一个风险模型的研究

研究了索赔到达过程为平稳无后效流,保单到达过程为平稳无后效流,并带扩散扰动项的盈余过程．讨论了该盈余过程的马尔科夫性和鞅性．然后用鞅方法得到其破产概率的表达式及其相应的Lundberg不等式．     

Model Based Design of a Novel Process for Nitrogen Removal from Concentrated Flows

A new process for biological nitrification was developed that is operated in a single aerated reactor at relatively high temperature and pH. This process, termed SHARON, was designed to achieve substantial ammonia conversion at high reaction rates for relatively concentrated flows, rather than to meet strict effluent standards. First large scale applications that are under construction now, aim at treating reject water from a sludge digestion unit. The SHARON process operates without sludge retention, and ammonium oxidation is stopped at nitrite, which saves on aeration costs. Denitrification is used as a cheap means to control the pH. Under typical conditions, no heating is necessary due to the heat production by the reactions. Overall processing costs are less than 50% of other techniques. This contribution focuses on model development for process design calculations at full scale. Underlying kinetic principles, and especially their pH dependency, are highlighted as well.     

Brillinger type mixing conditions for a simple branching diffusion process

A simple branching diffusion process is described. Formulae for intensity functions and factorial cumulant density functions at several times are given. Mixing conditions in terms of integrals of these cumulants are defined and proven for this stochastic evolutionary point process. The mixing conditions then allow a spatial central limit theorem and a strong law of large numbers to be easily obtained.     

Further results on convergence and stability of a generalization of the Richardson extrapolation process

In an earlier paper by the author a detailed convergence and stability analysis of a generalization of the Richardson extrapolation process was given under certain conditions. In the present work these conditions are modified and relaxed considerably, and results are obtained on convergence and stability under the new conditions. As the previous ones, these new results are asymptotic in nature, and contain the former. The conditions of the present paper are naturally satisfied, e.g., by the trapezoidal rule approximations of finite range integrals of functions having algebraic and logarithmic end point singularities.     

The convergence of the random lines defined by observations of a stochastic process

We deal with independent random variables which are the values of a stochastic process taken at random points in time. So we have random variables depending upon a random parameter. We obtain the conditions providing the weak convergence of random lines defined by sums or maxima or bilinear forms of these random variables for almost all values of the parameter, to one and the same stochastic process. These limit stochastic processes are described. Proceedings of the XVII Seminar on Stability Problems for Stochastic Models, Kazan, Russia, 1995, Part II.     

Universal Coefficient Theorems and a Paper of DINH THE LUC

The consequences of an ergodic assumption for mosaic processes of random convex polygons are explored in detail. Under certain regularity conditions on the “smallness” and “largeness” of polygons it is shown that the geometric characteristics of the so-called “typical” polygons do in fact exist. New formulae concerning these characteristics are given. The polygon process formed by a Poisson line process is considered as an example of the general theory and, as a result, certain properties of this example which were previously given heuristically, are proved. Edge effects are treated rigorously.     

Convergence of a non-failable mean-field particle system

The existing literature contains many examples of mean-field particle systems converging to the distribution of a Markov process conditioned to not hit a given set. In many situations, these mean-field particle systems are failable, meaning that they are not well defined after a given random time. Our first aim is to introduce an original mean-field particle system, which is always well defined and whose large number particle limit is, in all generality, the distribution of a process conditioned to not hit a given set. Under natural conditions on the underlying process, we also prove that the convergence holds uniformly in time as the number of particles goes to infinity. As an illustration, we show that our assumptions are satisfied in the case of a piece-wise deterministic Markov process.