부산대학교 도서관

Merging available sources of information is becoming increasingly important for improving estimates of population characteristics in a variety of fields. In presence of several independent probability samples from a finite population we investigate options for a combined estimator of the population total, based on either a linear combination of the separate estimators or on the combined sample approach. A linear combination estimator based on estimated variances can be biased as the separate estimators of the population total can be highly correlated to their respective variance estimators. We illustrate the possibility to use the combined sample to estimate the variances of the separate estimators, which results in general pooled variance estimators. These pooled variance estimators use all available information and have potential to significantly reduce bias of a linear combination of separate estimators. Key Words: Horvitz-Thompson estimator; Inclusion probabilities; Linear combination estimator; Variance estimation.
1 Introduction The idea of using all available information to produce better estimates is very appealing, but it is seldom clear how to proceed to achieve the best results. There [...]