Nonparametric Methods for Solving the Berkson Errors-in-Variables Problem

DOI10.1111/j.1467-9868.2006.00540.xzbMath1100.62044OpenAlexW2003992972MaRDI QIDQ3408532

Hall, Peter, Peihua Qiu, Aurore Delaigle

Publication date: 14 November 2006

Published in: Journal of the Royal Statistical Society Series B: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1467-9868.2006.00540.x

zbMATH Keywords

smoothingregularizationill-posed problemdeconvolutionkernel methodsmeasurement errortrigonometric series

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08)

Related Items (12)

Nonparametric estimation of cumulative distribution function from noisy data in the presence of Berkson and classical errors ⋮ Modeling body height in prehistory using a spatio-temporal Bayesian errors-in-variables model ⋮ Regressions with Berkson errors in covariates -- a nonparametric approach ⋮ Instrumental variable approach to covariate measurement error in generalized linear models ⋮ Estimation of nonparametric regression models with a mixture of Berkson and classical errors ⋮ Unnamed Item ⋮ Nonparametric regression estimate with Berkson Laplace measurement error ⋮ Nonparametric Berkson regression under normal measurement error and bounded design ⋮ Nonparametric density estimation from data with a mixture of Berkson and classical errors ⋮ Rate-optimal nonparametric estimation in classical and Berkson errors-in-variables problems ⋮ Nonparametric Kernel Methods with Errors-in-Variables: Constructing Estimators, Computing them, and Avoiding Common Mistakes ⋮ Simultaneous inference for Berkson errors-in-variables regression under fixed design

Cites Work

• Unnamed Item
• Unnamed Item
• Multivariate regression estimation with errors-in-variables: Asymptotic normality for mixing processes
• Berkson measurement error in designed repeated measures studies with random coefficients
• Empirical simulation extrapolation for measurement error models with replicate measurements.
• Semiparametric Regression Modeling with Mixtures of Berkson and Classical Error, with Application to Fallout from the Nevada Test Site
• Simulation extrapolation deconvolution of finite population cumulative distribution function estimators
• Optimal Change‐point Estimation in Inverse Problems
• Bayesian Smoothing and Regression Splines for Measurement Error Problems
• Local Polynomial Regression and Simulation–Extrapolation
• Low Order Approximations in Deconvolution and Regression with Errors in Variables
• Nonparametric Estimation of the Conditional Mode with Errors-In-Variables: Strong Consistency for Mixing Processes
• NONPARAMETRIC ESTIMATION WITH AGGREGATED DATA
• Nonparametric regression in the presence of measurement error

This page was built for publication: Nonparametric Methods for Solving the Berkson Errors-in-Variables Problem