MDP for estimators in EV regression models with α-mixing errors

DOI10.1080/02331888.2014.886689zbMath1395.62048OpenAlexW2015257518MaRDI QIDQ5263972

Shaochen Wang

Publication date: 20 July 2015

Published in: Unnamed Author (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331888.2014.886689

zbMATH Keywords

\(\alpha\)-mixingmoderate deviation principleLS estimatorEV models

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Linear regression; mixed models (62J05) Large deviations (60F10)

Related Items (1)

Strong consistency of least-squares estimators in the simple linear errors-in-variables regression model with widely orthant dependent random variables

Cites Work

• Unnamed Item
• Delta method in large deviations and moderate deviations for estimators
• Convergence rate for LS estimator in simple linear EV regression models
• Strong consistency of least squares estimates in multiple regression II
• Estimation for the multivariate errors-in-variables model with estimated error covariance matrix
• Panel data from time series of cross-sections
• Asymptotic properties of an estimator in nonlinear functional errors-in-variables models with dependent error terms
• Estimation in a multivariate errors in variables regression model: Large sample results
• Empirical likelihood confidence region for parameter in the errors-in-variables models.
• Moderate deviations for LS estimator in simple linear EV regression model
• Bernstein inequality and moderate deviations under strong mixing conditions
• A Consistent Estimator for Linear Models with Dependent Observations
• The loglog law for LS estimator in simple linear EV regression models
• The Central Limit Theorem for LS Estimator in Simple Linear EV Regression Models

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