A least square-type procedure for parameter estimation in stochastic differential equations with additive fractional noise

Nualart (2003): Stochastic integration with respect to the fractional Brownian motion. Pap (2011): Explicit formulas for Laplace transforms of certain functionals of some

A GENERAL DRIFT ESTIMATION PROCEDURE FOR STOCHASTIC DIFFERENTIAL EQUATIONS WITH ADDITIVE FRACTIONAL NOISE.. Electronic Journal of Statistics , Shaker Heights, OH : Institute

We investigate the problem of the rate of convergence to equilibrium for ergodic stochastic differential equations driven by fractional Brownian motion with Hurst parameter H ∈ (1/3,

Nualart (2003): Stochastic integration with respect to the fractional Brownian motion. Pap (2011): Explicit formulas for Laplace transforms of certain functionals of some

Other methods such as [6] or [11] are also able to compute guaranteed confidence regions using interval analysis, but the computed set is not of minimal volume and it is difficult

Second, the proposed framework provides a simple deterministic description for the LS estimation under noisy measurements where the noise can be of large magnitude.. Note that

We provide our main result on a rate of weak errors under SDEs with discontinuous drift and nonlinear diffusion coefficient in Section 3, and also give results under constant

Abstract: In this short note, we show how to use concentration inequalities in order to build exact confidence intervals for the Hurst parameter associated with a