Large deviations of regression parameter estimator in continuous-time models with sub-Gaussian noise
Volume 5, Issue 2 (2018): Testas Special Issue 2026, pp. 191–206
Pub. online: 7 May 2018
Type: Research Article
Open Access
Open Access
Received
31 January 2018
31 January 2018
Revised
19 April 2018
19 April 2018
Accepted
22 April 2018
22 April 2018
Published
7 May 2018
7 May 2018
Abstract
A continuous-time regression model with a jointly strictly sub-Gaussian random noise is considered in the paper. Upper exponential bounds for probabilities of large deviations of the least squares estimator for the regression parameter are obtained.
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