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Parameter estimation for threshold Ornstein–Uhlenbeck processes from discrete observations.
- Source :
-
Journal of Computational & Applied Mathematics . Sep2022, Vol. 411, pN.PAG-N.PAG. 1p. - Publication Year :
- 2022
-
Abstract
- Assuming that a threshold Ornstein–Uhlenbeck process is observed at discrete time instants, we propose generalized moment estimators to estimate the parameters. Our theoretical basis is the celebrated ergodic theorem. With the sampling time step arbitrarily fixed, we prove the strong consistency and asymptotic normality of our estimators as the sample size tends to infinity. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 03770427
- Volume :
- 411
- Database :
- Academic Search Index
- Journal :
- Journal of Computational & Applied Mathematics
- Publication Type :
- Academic Journal
- Accession number :
- 156506427
- Full Text :
- https://doi.org/10.1016/j.cam.2022.114264