Variable selection in measurement error models

From MaRDI portal
Publication:605044

DOI10.3150/09-BEJ205zbMath1200.62071arXiv1002.4329WikidataQ33704085 ScholiaQ33704085MaRDI QIDQ605044

Yanyuan Ma, Run-Ze Li

Publication date: 12 November 2010

Published in: Bernoulli (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1002.4329



Related Items

Hypothesis test for the parameters of linear part in the partial linear EV model, Model structure selection in single-index-coefficient regression models, De-noising boosting methods for variable selection and estimation subject to error-prone variables, Variable selection and inference procedures for marginal analysis of longitudinal data with missing observations and covariate measurement error, Generalized varying coefficient partially linear measurement errors models, Balanced estimation for high-dimensional measurement error models, NONPARAMETRIC SIGNIFICANCE TESTING IN MEASUREMENT ERROR MODELS, Variable selection in measurement error models, Corrected empirical likelihood for a class of generalized linear measurement error models, Variable selection in linear measurement error models via penalized score functions, L 0 -regularization for high-dimensional regression with corrupted data, Sparse estimation in high-dimensional linear errors-in-variables regression via a covariate relaxation method, Simultaneous variable selection and estimation in semiparametric modeling of longitudinal/clustered data, Scalable interpretable learning for multi-response error-in-variables regression, A two-component \(G\)-prior for variable selection, Covariate Selection in High-Dimensional Generalized Linear Models With Measurement Error, Inference in high dimensional linear measurement error models, Quantile regression in longitudinal studies with dropouts and measurement errors, Regularized matrix-variate logistic regression with response subject to misclassification, Independence tests in the presence of measurement errors: an invariance law



Cites Work