Adaptive prediction of non-Gaussian Ornstein-Uhlenbeck process T. V. Dogadova, V. A. Vasiliev
Material type:
ArticleOther title: Адаптивное прогнозирование негауссовского процесса Орнштейна-Уленбека [Parallel title]Subject(s): усеченное оценивание параметров | адаптивное оптимальное прогнозирование | Орнштейна-Уленбека негауссовский процессGenre/Form: статьи в журналах Online resources: Click here to access online
In:
Вестник Томского государственного университета. Управление, вычислительная техника и информатика № 43. С. 26-32Abstract: This paper proposes adaptive predictors of non-Gaussian Ornstein–Uhlenbeck process with unknown parameters. Predictors are based on the truncated parameter estimators. Asymptotic and non-asymptotic properties of the predictors are investigated. In particular, there is found the rate of convergence of the second moment of a prediction error to its minimum value. In addition, there is established an asymptotic optimality of the adaptive predictors in the sense of a special risk function. The structure of the risk function assumes the optimization of both the duration of observations and the prediction quality.
Библиогр.: 8 назв.
This paper proposes adaptive predictors of non-Gaussian Ornstein–Uhlenbeck process with unknown parameters. Predictors are based on the truncated parameter estimators. Asymptotic and non-asymptotic properties of the predictors are investigated. In particular, there is found the rate of convergence of the second moment of a prediction error to its minimum value. In addition, there is established an asymptotic optimality of the adaptive predictors in the sense of a special risk function. The structure of the risk function assumes the optimization of both the duration of observations and the prediction quality.
There are no comments on this title.