An Information-theoretic Approach to the Effective Usage of Auxiliary Information from Survey Data |
| |
Authors: | Changchun Wu Runchu Zhang |
| |
Affiliation: | (1) School of Mathematics and Information, Jiaxing University, Jiaxing, Zhejiang, 314001, China;(2) LPMC and School of Mathematical Sciences, Nankai University, Tianjin, 300071, China |
| |
Abstract: | In this paper, we propose an information-theoretic approach to the effective usage of auxiliary information from survey data, which is suitable for both simple and complex survey data. Our estimator under simple random sampling without replacement will be consistent and asymptotically normal. We show that the resulting estimates have smaller asymptotic variances than the usual estimates which do not use auxiliary information. For more complex survey designs, the resulting estimator is in essence asymptotically equivalent to a pseudo empirical likelihood estimator. Results of a limited simulation study show that the proposed estimators perform well among a number of competitors. |
| |
Keywords: | Calibration Entropy Cross-entropy Generalized regression estimator Empirical likelihood Optimal regression estimator Jackknife |
本文献已被 SpringerLink 等数据库收录! |
|