2013
DOI: 10.1111/biom.12059
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BAS: Balanced Acceptance Sampling of Natural Resources

Abstract: To design an efficient survey or monitoring program for a natural resource it is important to consider the spatial distribution of the resource. Generally, sample designs that are spatially balanced are more efficient than designs which are not. A spatially balanced design selects a sample that is evenly distributed over the extent of the resource. In this article we present a new spatially balanced design that can be used to select a sample from discrete and continuous populations in multi-dimensional space. … Show more

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Cited by 82 publications
(100 citation statements)
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“…In this section we modify the original BAS design of Robertson et al (2013) and show how the modified design achieves exact equi-probable samples from Halton frames. For simplicity, the modified design uses a random-start in the Targeted inclusion probabilities are not necessarily achieved with BAS because a variable number of BAS points are rejected for not selecting a unit at the very beginning of the sequence.…”
Section: Modification To Basmentioning
confidence: 99%
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“…In this section we modify the original BAS design of Robertson et al (2013) and show how the modified design achieves exact equi-probable samples from Halton frames. For simplicity, the modified design uses a random-start in the Targeted inclusion probabilities are not necessarily achieved with BAS because a variable number of BAS points are rejected for not selecting a unit at the very beginning of the sequence.…”
Section: Modification To Basmentioning
confidence: 99%
“…Natural resources are often spatially autocorrelated because nearby locations interact with one another and are influenced by the same factors (Stevens & Olsen,5 2004). Hence, spreading the sample over of the study area is known to be efficient, and many variations of spatially balanced designs have been proposed (Stevens & Olsen, 2004;Grafström et al, 2012;Robertson et al, 2013). This article considers balanced acceptance sampling (BAS) (Robertson et al, 2013).…”
Section: Introductionmentioning
confidence: 99%
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