Remote Access Theory of Probability and Mathematical Statistics

Theory of Probability and Mathematical Statistics

ISSN 1547-7363(online) ISSN 0094-9000(print)

 
 

 

Large deviations of regression parameter estimate in the models with stationary sub-Gaussian noise


Author: A. V. Ivanov
Original publication: Teoriya Imovirnostei ta Matematichna Statistika, tom 95 (2016).
Journal: Theor. Probability and Math. Statist. 95 (2017), 99-108
MSC (2010): Primary 60G50, 65B10, 60G15; Secondary 40A05
DOI: https://doi.org/10.1090/tpms/1024
Published electronically: February 28, 2018
Full-text PDF

Abstract | References | Similar Articles | Additional Information

Abstract: Exponential bounds for probabilities of large deviations of nonlinear regression parameter least squares estimate in the models with jointly strictly sub-Gaussian random noise are obtained.


References [Enhancements On Off] (What's this?)


Similar Articles

Retrieve articles in Theory of Probability and Mathematical Statistics with MSC (2010): 60G50, 65B10, 60G15, 40A05

Retrieve articles in all journals with MSC (2010): 60G50, 65B10, 60G15, 40A05


Additional Information

A. V. Ivanov
Affiliation: Department of Mathematical Analysis and Probability Theory, Faculty of Physics and Mathematics, NTUU“KPI”, Kyiv, Ukraine
Email: alexntuu@gmail.com

DOI: https://doi.org/10.1090/tpms/1024
Keywords: Large deviations, least squares estimate, nonlinear regression, discrete white sub-Gaussian noise, spectral density
Received by editor(s): August 29, 2016
Published electronically: February 28, 2018
Article copyright: © Copyright 2018 American Mathematical Society

American Mathematical Society