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Two-stage sequential sampling: A neighborhood-free adaptive sampling procedure

Journal of Agricultural, Biological, and Environmental Statistics

By:
,
DOI: 10.1198/108571105X28183

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Abstract

Designing an efficient sampling scheme for a rare and clustered population is a challenging area of research. Adaptive cluster sampling, which has been shown to be viable for such a population, is based on sampling a neighborhood of units around a unit that meets a specified condition. However, the edge units produced by sampling neighborhoods have proven to limit the efficiency and applicability of adaptive cluster sampling. We propose a sampling design that is adaptive in the sense that the final sample depends on observed values, but it avoids the use of neighborhoods and the sampling of edge units. Unbiased estimators of population total and its variance are derived using Murthy's estimator. The modified two-stage sampling design is easy to implement and can be applied to a wider range of populations than adaptive cluster sampling. We evaluate the proposed sampling design by simulating sampling of two real biological populations and an artificial population for which the variable of interest took the value either 0 or 1 (e.g., indicating presence and absence of a rare event). We show that the proposed sampling design is more efficient than conventional sampling in nearly all cases. The approach used to derive estimators (Murthy's estimator) opens the door for unbiased estimators to be found for similar sequential sampling designs. ?? 2005 American Statistical Association and the International Biometric Society.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Two-stage sequential sampling: A neighborhood-free adaptive sampling procedure
Series title:
Journal of Agricultural, Biological, and Environmental Statistics
DOI:
10.1198/108571105X28183
Volume
10
Issue:
1
Year Published:
2005
Language:
English
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
Journal of Agricultural, Biological, and Environmental Statistics
First page:
84
Last page:
103
Number of Pages:
20