Regressions with Berkson errors in covariates -- a nonparametric approach

DOI10.1214/13-AOS1122zbMath1292.62061arXiv1308.2836MaRDI QIDQ367002

Susanne M. Schennach

Publication date: 25 September 2013

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1308.2836

zbMATH Keywords

errors in variablesinstrumental variablesnonparametric inferencenonparametric maximum likelihoodBerkson measurement error

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Multivariate analysis (62H99)

Related Items (12)

Minimum distance partial linear regression model checking with Berkson measurement errors ⋮ Maximum entropy in the mean methods in propensity score matching for interval and noisy data ⋮ The econometrics of unobservables: applications of measurement error models in empirical industrial organization and labor economics ⋮ Sparse linear regression models of high dimensional covariates with non-Gaussian outliers and Berkson error-in-variable under heteroscedasticity ⋮ Regressions with Berkson errors in covariates -- a nonparametric approach ⋮ A minimum projected-distance test for parametric single-index Berkson models ⋮ Unnamed Item ⋮ Identification of mixture models using support variations ⋮ Minimum distance model checking in Berkson measurement error models with validation data ⋮ Performance of Wald-type estimator for parametric component in partial linear regression with a mixture of Berkson and classical error models ⋮ Identification of nonparametric monotonic regression models with continuous nonclassical measurement errors ⋮ Simultaneous inference for Berkson errors-in-variables regression under fixed design

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