Asymptotics for weakly dependent errors-in-variables

zbMath1278.15036arXiv1306.5311MaRDI QIDQ2868778

Michal Pešta

Publication date: 19 December 2013

Full work available at URL: https://arxiv.org/abs/1306.5311

zbMATH Keywords

asymptotic normalitydependent errorserrors-in-variables (EIV)total least squares (TLS)

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Linear inference, regression (62J99) Numerical computation of eigenvalues and eigenvectors of matrices (65F15) Random matrices (algebraic aspects) (15B52) Stochastic matrices (15B51)

Related Items (3)

Asymptotic normality of total least squares estimator in a multivariate errors-in-variables model \(AX = B\) ⋮ EIV regression with bounded errors in data: total `least squares' with Chebyshev norm ⋮ Changepoint in dependent and non-stationary panels

Cites Work

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• An Analysis of the Total Least Squares Problem
• Basic properties of strong mixing conditions. A survey and some open questions
• Estimation in a multivariate errors in variables regression model: Large sample results
• Total least squares and bootstrapping with applications in calibration
• On the Central Limit Theorem for $\varphi$-Mixing Arrays of Random Variables
• A functional central limit theorem for strongly mixing sequences of random variables
• Consistency of regression estimates when some variables are subject to error

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