title: 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. The design, which we call balanced acceptance sampling, utilizes the Halton sequence to assure spatial diversity of selected locations. Targeted inclusion probabilities are achieved by acceptance sampling. The BAS design is conceptually simpler than competing spatially balanced designs, executes faster, and achieves better spatial balance as measured by a number of quantities. The algorithm has been programed in an R package freely available for download.
authors.affiliation: Department of Mathematics and Statistics, University of Canterbury, Private Bag 4800, Christchurch, New Zealand.
authors.forename: B L
authors.initials: BL
authors.lastname: Robertson
authors.forename: J A
authors.initials: JA
authors.lastname: Brown
authors.forename: T
authors.initials: T
authors.lastname: McDonald
authors.forename: P
authors.initials: P
authors.lastname: Jaksons
mesh_terms: D000465:Algorithms; D001699:Biometry / Q000379:methods; D003198:Computer Simulation; D003247:Conservation of Natural Resources / Q000706:statistics & numerical data*; D004784:Environmental Monitoring / Q000706:statistics & numerical data*; D015233:Models, Statistical; D018401:Sample Size
keywords: Environmental sampling; Halton sequence; Spatially balanced sampling; Unequal 
  probability sampling