Convergence of estimators in the polynomial measurement error model

DOI10.1090/tpms/984zbMath1343.62009OpenAlexW2499173701MaRDI QIDQ2817051

Alexander G. Kukush, Ya. V. Tsaregorodtsev

Publication date: 29 August 2016

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

Full work available at URL: https://doi.org/10.1090/tpms/984

zbMATH Keywords

asymptotic normalitypolynomial regressionmeasurement error modelconsistency of estimatorsadjusted least squares estimatormodification of estimators for small samples

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) General nonlinear regression (62J02)

Related Items (1)

Prediction in polynomial errors-in-variables models

Cites Work

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• Consistency of an adjusted least-squares estimator in a vector linear model with measurement errors
• The efficiency of adjusted least squares in the linear functional relationship.
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• Testing the suitability of polynomial models in errors-in-variables problems
• The asymptotic normality of an adjusted least squares estimator in a multivariate vector errors-in-variables regression model
• Polynomial Regression With Errors in the Variables
• A Small Sample Estimator for a Polynomial Regression with Errors in the Variables
• Comparing the efficiency of structural and functional methods in measurement error models
• Generalized two-parameter Lebesgue-Stieltjes integrals and their applications to fractional Brownian fields

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