Large deviations of regression parameter estimator in continuous-time models with sub-Gaussian noise
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.
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
VTeX
2018-05-01
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| Series: | Modern Stochastics: Theory and Applications |
| Subjects: | |
| Online Access: | https://vmsta.vtex.vmt/doi/10.15559/18-VMSTA102 |