Some methods to improve the utility of conditioned Latin hypercube sampling

@inproceedings{Malone2019SomeMT,
  title={Some methods to improve the utility of conditioned Latin hypercube sampling},
  author={Brendan P. Malone and Budiman Minansy and Colby W. Brungard},
  booktitle={PeerJ},
  year={2019}
}
The conditioned Latin hypercube sampling (cLHS) algorithm is popularly used for planning field sampling surveys in order to understand the spatial behavior of natural phenomena such as soils. This technical note collates, summarizes, and extends existing solutions to problems that field scientists face when using cLHS. These problems include optimizing the sample size, re-locating sites when an original site is deemed inaccessible, and how to account for existing sample data, so that under… CONTINUE READING
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