Campus Units
Statistics
Document Type
Article
Publication Version
Published Version
Publication Date
1-2009
Journal or Book Title
Statistica Sinica
Volume
19
Issue
1
First Page
145
Last Page
157
Abstract
Calibration estimation, which can be roughly described as adjusting the original design weights to incorporate the known population totals of the auxiliary variables, has become very popular in sample surveys.The calibration weights are chosen to minimize a given distance measure while satisfying a set of constraints related to the auxiliary variable information. Under simple random sampling, Chen and Qin (1993) suggested that the calibration estimator maximizing the constrained empirical likelihood can make efficient use of the auxiliary variables. We extend the result to unequal probability sampling and propose an algorithm to implement the proposed procedure. Asymptotic properties of the proposed calibration estimator are discussed. The proposed method is extended to the stratified sampling. Results from a limited simulation study are presented.
Copyright Owner
Institute of Statistical Science, Academia Sinica
Copyright Date
2009
Language
en
File Format
application/pdf
Recommended Citation
Kim, Jae Kwang, "Calibration estimation using empirical likelihood in survey sampling" (2009). Statistics Publications. 98.
https://lib.dr.iastate.edu/stat_las_pubs/98
Included in
Design of Experiments and Sample Surveys Commons, Statistical Methodology Commons, Statistical Models Commons
Comments
This is an article published as Kim, Jae Kwang. "Calibration estimation using empirical likelihood in survey sampling." Statistica Sinica (2009): 145-157. Posted with permission.