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A review of adaptive cluster sampling: 1990–2003

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Abstract

Adaptive cluster sampling (ACS) is an adaptive sampling scheme which operates under the rule that when the observed value of an initially selected sampling unit satisfies some condition of interest, C, other additional units in some pre-defined accompanying neighborhood are also added to the sample. In turn, if any of these additional units satisfy C, then their corresponding unit neighborhoods are added to the sample as well, and so on. This process stops when no additional units satisfying C are encountered. This paper will provide a review of the major developments and issues in ACS since its introduction by Thompson (1990) [Journal of the American Statistical Association, 85, 1050–1059].

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  1. Department of Mathematical Sciences, Montana State University, Bozeman, 59717, MT, USA

    PHILIP TURK & JOHN J. BORKOWSKI

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  1. PHILIP TURK
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  2. JOHN J. BORKOWSKI
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TURK, P., BORKOWSKI, J.J. A review of adaptive cluster sampling: 1990–2003. Environ Ecol Stat 12, 55–94 (2005). https://doi.org/10.1007/s10651-005-6818-0

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