Characterization theorems when variables are measured with error

DOI10.1006/jmva.1998.1796zbMath0927.62070OpenAlexW2044405720MaRDI QIDQ1283928

John P. jun. Holcomb

Publication date: 13 December 1999

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1006/jmva.1998.1796

zbMATH Keywords

conditional expectationconditional variancemeasurement error model

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Characterization and structure theory for multivariate probability distributions; copulas (62H05)

Related Items (2)

Linear EV model with replicate observations on independent variables ⋮ Bivariate, multivariate, and matrix variate normal characterizations: A brief survey II

Uses Software

• BLINPLUS
• relibpls8

Cites Work

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• Deconvolution-based score tests in measurement error models
• Covariate measurement error in logistic regression
• Natural exponential families with quadratic variance functions
• On a problem connected with quadratic regression
• A Semiparametric Correction for Attenuation
• Errors of Measurement in Statistics
• Note on a Problem of Ragnar Frisch
• REGRESSION, STRUCTURE AND FUNCTIONAL RELATIONSHIP. PART I
• REGRESSION, STRUCTURE AND FUNCTIONAL RELATIONSHIP. PART II

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