dataset · 2012

clhs: Conditioned Latin Hypercube Sampling

Cited by 43Open access

Abstract

Conditioned Latin hypercube sampling, as published by Minasny and McBratney (2006) <<a href="https://doi.org/10.1016%2Fj.cageo.2005.12.009" target="_top">doi:10.1016/j.cageo.2005.12.009</a>>. This method proposes to stratify sampling in presence of ancillary data. An extension of this method, which propose to associate a cost to each individual and take it into account during the optimisation process, is also proposed (Roudier et al., 2012, <<a href="https://doi.org/10.1201%2Fb12728" target="_top">doi:10.1201/b12728</a>>).

Cite this paper

APA 7

Roudier, P. (2012). clhs: Conditioned Latin Hypercube Sampling. https://doi.org/10.32614/cran.package.clhs

MLA 9

Roudier, Pierre. “clhs: Conditioned Latin Hypercube Sampling.” 2012, https://doi.org/10.32614/cran.package.clhs.

Chicago

Roudier, Pierre. 2012. “clhs: Conditioned Latin Hypercube Sampling.” https://doi.org/10.32614/cran.package.clhs.

Harvard

Roudier, P. (2012) ‘clhs: Conditioned Latin Hypercube Sampling’. Available at: https://doi.org/10.32614/cran.package.clhs.

BibTeX

@misc{roudier2012clhs,
  title = {{clhs: Conditioned Latin Hypercube Sampling}},
  author = {Roudier, Pierre},
  year = {2012},
  doi = {10.32614/cran.package.clhs}
}

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