Low Order Approximations in Deconvolution and Regression with Errors in Variables

From MaRDI portal
Publication:4665829

DOI10.1111/j.1467-9868.2004.00430.xzbMath1062.62066OpenAlexW1994420078MaRDI QIDQ4665829

Hall, Peter, Raymond J. Carroll

Publication date: 11 April 2005

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.1467-9868.2004.00430.x



Related Items

Moment adjusted imputation for multivariate measurement error data with applications to logistic regression, Estimating the total rate of DNA replication using branching processes, Bayesian semiparametric regression in the presence of conditionally heteroscedastic measurement and regression errors, Wavelet estimations for heteroscedastic super smooth errors, Density estimation for circular data observed with errors, Kernel regression for errors-in-variables problems in the circular domain, Power spectrum unbiasing for dilation-invariant multi-reference alignment, SIMEX and standard error estimation in semiparametric measurement error models, Asymptotics for TAYLEX and SIMEX estimators in deconvolution of densities, t-Type corrected-loss estimation for error-in-variable model, Survival and aging in the wild via residual demography, Accelerated convergence for nonparametric regression with coarsened predictors, A SPECTRAL METHOD FOR DECONVOLVING A DENSITY, Multiple Testing of Composite Null Hypotheses in Heteroscedastic Models, Unnamed Item, Rate-optimal nonparametric estimation in classical and Berkson errors-in-variables problems, Bayesian Semiparametric Multivariate Density Deconvolution, Nonparametric Kernel Methods with Errors-in-Variables: Constructing Estimators, Computing them, and Avoiding Common Mistakes, Density estimation with heteroscedastic error, Corrected-loss estimation for error-in-variable partially linear model, Semiparametric Density Deconvolution, Nonparametric Methods for Solving the Berkson Errors-in-Variables Problem



Cites Work