Efficient population mean estimation of sensitive traits using robust quantile regression and scrambled response methodology
Using robust regression approach for mean estimation in survey sampling with a single supplementary information is a well-established practice when there are outliers in the data set. The most popular methods for sensitive studies are regression estimation methods that use standard regression coeffi...
Saved in:
Main Authors: | Abdulaziz S. Alghamdi, Marwan H. Alhelali |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2025-10-01
|
Series: | Alexandria Engineering Journal |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016825007501 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Kernel Density Estimation for Joint Scrambling in Sensitive Surveys
by: Alvan Caleb Arulandu, et al.
Published: (2025-06-01) -
Sinkhorn Distributionally Robust Conditional Quantile Prediction with Fixed Design
by: Guohui Jiang, et al.
Published: (2025-05-01) -
Imputation of missing data for domain mean estimation using simple random sampling
by: Anoop Kumar, et al.
Published: (2025-10-01) -
Robust Variable Selection via Bayesian LASSO-Composite Quantile Regression with Empirical Likelihood: A Hybrid Sampling Approach
by: Ruisi Nan, et al.
Published: (2025-07-01) -
An improved class of estimators for mean estimation of finite population in simple random sampling
by: Jiawei Yao, et al.
Published: (2025-10-01)