Monte Carlo methods for nonparametric regression with heteroscedastic measurement error-Reference-Cited by-同舟云学术

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Monte Carlo methods for nonparametric regression with heteroscedastic measurement error

Published:2017-09-15 Issue:2 Volume:74 Page:498-505
ISSN:0006-341X
Container-title:Biometrics
language:en
Short-container-title:Biom

Author:

McIntyre Julie¹^ORCID,Johnson Brent A.²,Rappaport Stephen M.³

Affiliation:

1. Department of Mathematics and Statistics; University of Alaska Fairbanks; Fairbanks, Alaska 99775 U.S.A.

2. Department of Biostatistics and Computational Biology; University of Rochester; Rochester, New York 14642 U.S.A.

3. Department of Environmental Health Sciences; University of California; Berkeley, California 94720 U.S.A.

Publisher

Wiley

Subject

Applied Mathematics,General Agricultural and Biological Sciences,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,Statistics and Probability

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/biom.12765/fullpdf

Reference28 articles.

1. Bayesian Smoothing and Regression Splines for Measurement Error Problems

2. Low-order approximations in deconvolution and regression with errors in variables;Carroll;Journal of the Royal Statistical Society, Series B,2004

3. Nonparametric regression in the presence of measurement error;Carroll;Biometrika,1999

4. Nonlinear and nonparametric regression and instrumental variables;Carroll;Journal of the American Statistical Association,2004

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