Add to ORKGIn this paper for real Gaussian stochastic processes including Brownian bridge the approximate formulas for calculating its expectation values and dispersions are obtained. Numerical examples of calculation of the expectation values for the specific functions of stochastic Ornstein-Uhlenbeck process are constructed. A class of stochastic processes, the mathematical expectation of which is defined by Bernstein polynomials is considered. E. V. Voronovskaya’s formula concerning the asymptotic specification of function approximations by Bernstein polynomials has been applied for this case
The stochastic Bernstein method (not to be confused with the Bernstein polynomials) is a novel and s...
From some time past our interest was focused to find new possibilities for characterizing the proces...
Likelihood functional for stochastic linear time-delayed systems involve Itô integrals with respect ...
In this paper for real Gaussian stochastic processes including Brownian bridge the approximate formu...
Some simple approximate formulae for mathematical expectations of random nonlinear functionals are ...
The approximate calculation of functionals of a special type, which depends on a trajectory of a sto...
In this paper stochastic differential equations with a drift are considered. Approximate formula for ...
Two methods of modeling for the Ornstein-Uhlenbeck process are studied in the work. This process has...
Approximate formulas for evaluation of mathematical expectation of nonlinear functionals of solution...
Stochastic analysis is the analysis of functionals defined on the Wiener space, i.e., the space on w...
Abstract In this paper, models that approximate stochastic processes from the space Subφ(Ω) with giv...
AbstractMotivated by asymptotic problems in the theory of empirical processes, and specifically by t...
We consider a linear stochastic differential equation with stochastic drift. We study the problem of...
An asymptotic expansion scheme in finance initiated by Kunitomo and Takahashi [15] and Yoshida[68] i...
In the Thesis we study the Ornstein-Uhlenbeck Bridges. First, we recall the notion of the fractional...
The stochastic Bernstein method (not to be confused with the Bernstein polynomials) is a novel and s...
From some time past our interest was focused to find new possibilities for characterizing the proces...
Likelihood functional for stochastic linear time-delayed systems involve Itô integrals with respect ...
In this paper for real Gaussian stochastic processes including Brownian bridge the approximate formu...
Some simple approximate formulae for mathematical expectations of random nonlinear functionals are ...
The approximate calculation of functionals of a special type, which depends on a trajectory of a sto...
In this paper stochastic differential equations with a drift are considered. Approximate formula for ...
Two methods of modeling for the Ornstein-Uhlenbeck process are studied in the work. This process has...
Approximate formulas for evaluation of mathematical expectation of nonlinear functionals of solution...
Stochastic analysis is the analysis of functionals defined on the Wiener space, i.e., the space on w...
Abstract In this paper, models that approximate stochastic processes from the space Subφ(Ω) with giv...
AbstractMotivated by asymptotic problems in the theory of empirical processes, and specifically by t...
We consider a linear stochastic differential equation with stochastic drift. We study the problem of...
An asymptotic expansion scheme in finance initiated by Kunitomo and Takahashi [15] and Yoshida[68] i...
In the Thesis we study the Ornstein-Uhlenbeck Bridges. First, we recall the notion of the fractional...
The stochastic Bernstein method (not to be confused with the Bernstein polynomials) is a novel and s...
From some time past our interest was focused to find new possibilities for characterizing the proces...
Likelihood functional for stochastic linear time-delayed systems involve Itô integrals with respect ...