On sequential estimation of the parameters of continuous-time trigonometric regression

Abstract

Consideration was given to the problem of estimating the parameters of a trigonometric regression with the Gaussian Ornstein–Uhlenbeck noise. One-step sequential estimation procedure with a special stopping time defined by a sample Fischer information matrix was proposed. It ensures a given mean square accuracy of estimates uniformly over some parametric region. The results of Monte Carlo simulation of the sequential procedure were presented and compared with the maximum likelihood estimates.