Adaptive cluster sampling is a specialized statistical method designed to enhance the effectiveness of sur-veys, particularly when the population or phenomena of interest is rare or …

The results and examples in this article show that adaptive cluster sampling strategies give lower variance than conventional strategies for certain types of populations and, in particular, …

Jan 15, 2025 · For rare and clustered populations, Thompson introduced ACS as an effective sampling method when data is not contaminated with outliers.

Mar 1, 2025 · Adaptive cluster sampling (ACS) is an efficient sampling technique for studying populations where the characteristic of interest is rare or spatially clustered. This method is …

Adaptive cluster sampling is considered in situations where the characteristic of interest is sparsely distributed but highly aggregated (clustered).

Section 10.2 introduces the notations and terminology used in adaptive cluster sampling (ACS).

Adaptive cluster sampling designs were proposed as a method that could be used when sampling rare populations whose units tend to appear in clusters. The resulting estimator is not based …

May 1, 2013 · When using adaptive cluster sampling (ACS), if an observed value of a sampling unit satisfies some condition of interest C, then additional units in a defined neighborhood are …

Feb 5, 2025 · On use of adaptive cluster sampling for variance estimation. Adaptive cluster sampling is particularly helpful whenever the target population is unique, dispersed unevenly, …

Situations when field researchers are tempted to deviate from preselected sampling plan and to include nearby or related units in sample, then adaptive cluster sampling (ACS) offers a nearly …