Large deviations of regression parameter estimator in continuous-time models with sub-Gaussian noise
arXiv:1806.03842 · doi:10.15559/18-VMSTA102
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.
Published at https://doi.org/10.15559/18-VMSTA102 in the Modern Stochastics: Theory and Applications (https://www.i-journals.org/vtxpp/VMSTA) by VTeX (http://www.vtex.lt/)