Modified regression estimators using robust regression methods and covariance matrices in stratified random sampling

DOI10.1080/03610926.2019.1588324OpenAlexW2934685878WikidataQ128102023 ScholiaQ128102023MaRDI QIDQ5077429

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Publication date: 18 May 2022

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2019.1588324

zbMATH Keywords

regression-type estimatorsauxiliary informationrelative efficiencystratified random samplingrobust regression methodsrobust covariance matrices

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (9)

Ratio-type estimators for improving mean estimation using Poisson regression method ⋮ An exponential family of median based estimators for mean estimation with simple random sampling scheme ⋮ Robust-regression-type estimators for improving mean estimation of sensitive variables by using auxiliary information ⋮ Memory type estimators of population mean using exponentially weighted moving averages for time scaled surveys ⋮ An improved class of robust ratio estimators by using the minimum covariance determinant estimation ⋮ A novel family of variance estimators based on L-moments and calibration approach under stratified random sampling ⋮ An efficient family of robust-type estimators for the population variance in simple and stratified random sampling ⋮ Generalized robust-regression-type estimators under different ranked set sampling ⋮ Imputation based mean estimators in case of missing data utilizing robust regression and variance–covariance matrices

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• Modified ratio estimators using robust regression methods
• The evaluation of socio-economic development of development agency regions in Turkey using classical and robust principal component analyses
• A General Qualitative Definition of Robustness

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