Shrinkage strategy in stratified random sample subject to measurement error
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Publication:625026
DOI10.1016/j.spl.2010.10.020zbMath1205.62035OpenAlexW2056465578MaRDI QIDQ625026
Publication date: 11 February 2011
Published in: Statistics \& Probability Letters (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.spl.2010.10.020
Estimation in multivariate analysis (62H12) Nonparametric estimation (62G05) Sampling theory, sample surveys (62D05) Monte Carlo methods (65C05)
Related Items (3)
Optimal method in multiple regression with structural changes ⋮ On shrinkage estimators in matrix variate elliptical models ⋮ A class of Stein-rules in multivariate regression model with structural changes
Cites Work
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- Preliminary test ridge regression estimators with Student's \(t\) errors and conflicting test-statis\-tics
- High order approximation for the coverage probability by a confident set centered at the positive-part James-Stein estimator
- Robust inference strategy in the presence of measurement error
- A pseudo empirical likelihood approach for stratified samples with nonresponse
- On preliminary test and shrinkage M-estimation in linear models
- Empirical likelihood and general estimating equations
- The asymptotic distributions of empirical likelihood ratio statistics in the presence of measurement error
- Empirical likelihood inference under stratified random sampling in the presence of measurement error
- Empirical likelihood inference in the presence of measurement error
- Empirical likelihood inference under stratified random sampling using auxiliary population information
- Risk comparison of some shrinkage M-estimators in linear models
- Improved nonparametric estimation of location vectors in multivariate regression models
- Estimating equations, empirical likelihood and constraints on parameters
- Shrinkage drift parameter estimation for multi‐factor Ornstein–Uhlenbeck processes
- Optimum Critical Value for Pre-Test Estimator
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