A finite population quantile estimation by unequal probability sampling. Issue 22 (16th November 2020)

• Record Type: Journal Article
• Authors: Chaudhuri, Arijit; Shaw, Purnima
• Is Part Of: Communications in statistics. Volume 49:Issue 22(2020)
• Page Start: 5419
• Page End: 5426
• Publication Date: 2020-11-16
• Subjects: Distribution function -- model -- predictor -- quantile -- super-population -- varying probability sample-selection; 62 DO5; Mathematical statistics -- Periodicals; Mathematics; Statistics; 519.2
• DOI: 10.1080/03610926.2019.1618475
• Languages: English
• ISSNs: 0361-0926

Abstract

Abstract: Using a model-assisted approach, this paper studies asymptotically design-unbiased (ADU) estimation of a population "distribution function" and extends to deriving an asymptotic and approximate unbiased estimator for a population quantile from a sample chosen with varying probabilities. The respective asymptotic standard errors and confidence intervals are then worked out. Numerical findings based on an actual data support the theory with efficient results.