A recently developed measure-theoretic framework solves a stochastic inverse problem (SIP) for models where uncertainties in model output data are predominantly due to aleatoric (i.e., irreducible) inputs parameters). The subsequent inferential target is distribution on parameters. Another type of quantify estimates “true” parameter values under the assumption that such should be reduced as mor...

In this paper, a novel methodology for estimating the parameters of robotic manipulator systems is proposed. It can be seen that, purpose parameter estimation, input torque to each joint motor designed as linear combination sinusoids. After transient responses angles exponentially converge zero, steady states angle outputs extracted. Since are equivalent finite Fourier series, coefficients stat...

In this paper, we construct consistent statistical estimators of the Hurst index, volatility coefficient, and drift parameter for Bessel processes driven by fractional Brownian motion with H<1/2. As an auxiliary result, also prove continuity process. The results are illustrated simulations.