A new family of robust quantile-regression-based mean estimators using Sarndal approach-Reference-Cited by-同舟云学术

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A new family of robust quantile-regression-based mean estimators using Sarndal approach

Published:2024-06-04 Issue: Volume: Page:1-20
ISSN:0361-0918
Container-title:Communications in Statistics - Simulation and Computation
language:en
Short-container-title:Communications in Statistics - Simulation and Computation

Author:

Anas Malik Muhammad¹^ORCID,Huang Zhengsheng¹,Shahzad Usman²³,Iftikhar Soofia⁴

Affiliation:

1. School of Mathematics and Statistics, Nanjing University of Science and Technology, Nanjing, Jiangsu, P.R. China

2. Department of Mathematics and Statistics, International Islamic University, Islamabad, Pakistan

3. Department of Mathematics and Statistics, PMAS-Arid Agriculture University, Rawalpindi, Pakistan

4. Department of Statistics, Shaheed Benazir Bhutto Women University Peshawar, Peshawa, KP, Pakistan

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/03610918.2024.2359504

Reference30 articles.

1. Robust-regression-type estimators for improving mean estimation of sensitive variables by using auxiliary information

2. Compromised-Imputation and EWMA-Based Memory-Type Mean Estimators Using Quantile Regression

3. Ratio estimation of the population mean using auxiliary information in simple random sampling and median ranked set sampling

4. On optimal classes of estimators under ranked set sampling

5. An improved class of robust ratio estimators by using the minimum covariance determinant estimation

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