Theory of Stochastic Processes

Aims & Scope

Theory of Stochastic Processes is a semi-annual journal publishing original articles and surveys on modern topic of the theory of stochastic processes and papers devoted to its applications to physics, biology, economics, computer sciences and engineering.

Metrics & Ranking

Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar

Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Mathematics, designed to support cutting-edge academic discovery.

Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Recursive and non-recursive regression estimators using Bernstein polynomials

  Citation: 2

  Authors: Y., A.

• Representations of the finite-dimensional point densities in Arratia flows with drift

  Citation: 1

  Authors: A.A., N.B.

• Strong consistency of the mode of multivariate recursive kernel density estimator under strong mixing hypothesis

  Citation: 1

  Authors: Fatma Ben, Yousri

• On a limit behaviour of a random walk penalised in the lower half-plane

  Citation: 1

  Authors: A., O. O.

• On number of particles in coalescing-fragmentating Wasserstein dynamics

  Citation: 1

  Authors: Vitalii

• On asymptotic behavior of solutions of stochastic differential equations in multidimensional space

  Citation: 1

  Authors: V. K.

• General inference in semiparametric models through divergences and the duality technique with applications

  Citation: 0

  Authors: Salim, Mohamed

• Geometric invariants of random link

  Citation: 0

  Authors: Y.

• Loop-erased random walks associated with Markov processes

  Citation: 0

  Authors: A.A., I.I.

• Asymptotics of error probabilities of optimal tests

  Citation: 0

  Authors: V., K.