Large deviations of regression parameter estimator in continuous-time models with sub-Gaussian noise
Probability
2018-06-12 v1
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.
Cite
@article{arxiv.1806.03842,
title = {Large deviations of regression parameter estimator in continuous-time models with sub-Gaussian noise},
author = {Alexander V. Ivanov and Igor V. Orlovskyi},
journal= {arXiv preprint arXiv:1806.03842},
year = {2018}
}
Comments
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/)