Abstract

Sample coordination seeks to create a probabilistic dependence between the selection of two or more samples drawn from the same population or from overlapping populations. Positive coordination increases the expected sample overlap, while negative coordination decreases it. There are numerous applications for sample coordination with varying objectives. A spatially balanced sample is a sample that is well-spread in some space. Forcing a spread within the selected samples is a general and very efficient variance reduction technique for the Horvitz-Thompson estimator. The local pivotal method and the spatially correlated Poisson sampling are two general schemes for achieving well-spread samples. We aim to introduce coordination for these sampling methods based on the concept of permanent random numbers. The goal is to coordinate such samples while preserving spatial balance. The proposed methods are motivated by examples from forestry, environmental studies, and official statistics.

Keywords

Coordination; Local pivotal method; Spatially correlated Poisson sampling; Permanent random numbers; Unequal probability sampling designs; Transformed spatially correlated Poisson sampling

Published in

Survey Methodology
2018, Volume: 44, number: 2, pages: 215-238

SLU Authors

• Grafström, Anton

  • Department of Forest Resource Management, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Probability Theory and Statistics


Permanent link to this page (URI)

https://res.slu.se/id/publ/98108