• A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site
Of all publications in the section: 6
Sort:
by name
by year
Article
Blank M. Markov Processes and Related Fields. 2012. Vol. 18. P. 531-552.

We study discrete time totally asymmetric exclusion process (TASEP) describing collective random walk of countable particle configurations in heterogeneous continuum. A typical example of this sort is a traffic flow model with obstacles: traffic lights, speed bumps, spatially varying local velocities etc. Ergodic properties of such systems are studied, in particular we obtain the so called Fundamental Diagram: dependence of average particle velocities on particles and obstacles densities and jump probabilities. The main technical tool is a "dynamical" coupling construction applied in a nonstandard fashion: instead of proving the existence of the successful coupling (which even might not hold) we use its presence/absence as an important diagnostic tool. This techniques allows to reduce the calculation of the average velocity to the similar problem for an auxiliary lattice zero-range process.

Added: Nov 26, 2014
Article
Molchanov S., Pastur L., Ray E. Markov Processes and Related Fields. 2015. Vol. 21. No. 3. P. 713-749.
Added: Jun 22, 2016
Article
Veretennikov A. Markov Processes and Related Fields. 2019. Vol. 25. P. 745-761.

Conditions for positive and polynomial recurrence have been proposed for a class of reliability models of two elements with transitions from working state to failure and back. As a consequence, uniqueness of stationary distribution of the model is proved; the rate of convergence towards this distribution may be theoretically evaluated on the basis of the established recurrence.

Added: Oct 29, 2019
Article
T.Belkina. Markov Processes and Related Fields. 2014. Vol. 20. No. 3. P. 505-525.
We consider two models of an insurance company which can invest its surplus in a risk free asset and in a risky asset with the price following the geometric Brownian motion. In the first model the surplus without in- vestment is governed by the classical Cram´er – Lundberg risk process. In the second model it is governed by the risk process with stochastic premiums. For the case when the insurance company invests in the risky asset only at a fixed leveraging level, we prove so called sufficiency theorems for the survival probability. These theorems state that the solutions of singular problems for linear integro-differential equations (IDEs), generated by infinitesimal operators of the resulting surplus processes, define the corresponding survival probabilities. The sufficiency theorems allow us to use a unified approach, based on the existence theorems and martingale methods. This approach also eliminates need to proof twice continuously differentiability of the survival probability as well as to use upper and lower bounds evaluation to specify asymptotic representations for the ruin probability. We also give a brief discussion of the papers, where the existence theorems for the considered problems in the case of exponential claim and premium distributions were proved. As a result, the solving of above sin- gular problems for IDEs leads to calculation of the survival probability as a function of the initial surplus on all nonnegative semi-axis and to obtaining of its asymptotic representations for large and small values of the surplus. We also demonstrate an application of some results concerning the asymptotic expansions at zero for linear IDE solutions to study optimal investment problem with limited leveraging level for the Cram´er – Lundberg model.
Added: May 20, 2015
Article
Veretennikov A., Zverkina G. Markov Processes and Related Fields. 2014. Vol. 20. No. 3. P. 479-504.

p, li { white-space: pre-wrap; }

An elementary rigorous justification of Dynkin's identity with an extended generator

based on the idea of a complete probability formula

is given for

queueing systems with a single server and discontinuous intensities of arrivals and service.

This formula is applied

to the analysis of ergodicity and, in particular, to polynomial

bounds of convergence rate to stationary distribution.

Added: Oct 18, 2014
Article
Grabchak M., Molchanov S. Markov Processes and Related Fields. 2019. Vol. 25. No. 4. P. 591-613.

In this paper we introduce the alloy model, which is a variant of Derrida’s random energy model (REM). The alloy model assumes that energy levels are independent and identically distributed (iid) random variables, whose distribution is a mixture of two distribution from the same location-scale family. These families are assumed to have either Weibull or Gumbel tails. Particular attention is paid to the case of normal distributions. For these we get more explicit results, which show that, for certain choices of the parameters, we can have two phase transitions, one first order and one second order.

Added: Nov 15, 2019