Large deviations of regression parameter estimator in continuous-time models with sub-Gaussian noise
Alexander V. Ivanov, Igor V. Orlovskyi
Modern Stochastics: Theory and Applications · 2018
doi:10.15559/18-vmsta102 (opens in a new tab)
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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.
Abstract licence: CC BY
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