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

DOI10.1090/tpms/1024zbMath1390.60109OpenAlexW2792273051WikidataQ130180886 ScholiaQ130180886MaRDI QIDQ4606861

No author found.

Publication date: 9 March 2018

Published in: Theory of Probability and Mathematical Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1090/tpms/1024

zbMATH Keywords

large deviationsnonlinear regressionspectral densityleast squares estimatediscrete white sub-Gaussian noise

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Gaussian processes (60G15) Large deviations (60F10)

Related Items (2)

Large deviations of regression parameter estimator in continuous-time models with sub-Gaussian noise ⋮ Large deviation inequalities of Bayesian estimator in nonlinear regression models

Uses Software

• itsmr

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• The large deviation for the least squares estimator of nonlinear regression model based on WOD errors
• A large deviation result for the least squares estimators in nonlinear regression
• The rate of convergence of the least squares estimator in a non-linear regression model with dependent errors
• On the exponential rate of convergence of the least squares estimator in the nonlinear regression model with Gaussian errors
• A large deviation result for parameter estimators and its application to nonlinear regression analysis
• Large deviation for a least squares estimator in a nonlinear regression model
• On the measurability and consistency of minimum contrast estimates
• An Asymptotic Expansion for the Distribution of the Least Squares Estimator of the Non-Linear Regression Parameter
• Introduction to Time Series and Forecasting

This page was built for publication: Large deviations of regression parameter estimate in the models with stationary sub-Gaussian noise