clhs: Conditioned Latin Hypercube Sampling

Conditioned Latin hypercube sampling, as published by Minasny and McBratney (2006) <doi:10.1016/j.cageo.2005.12.009>. 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, <doi:10.1201/b12728>).

Version: 0.9.0
Depends: R (≥ 2.14.0)
Imports: utils, methods, grid, ggplot2, sp, sf, raster, reshape2, plyr, cluster, Rcpp
LinkingTo: RcppArmadillo, Rcpp
Suggests: knitr, rmarkdown, testthat
Published: 2021-10-14
DOI: 10.32614/CRAN.package.clhs
Author: Pierre Roudier [aut, cre], Colby Brugnard [ctb], Dylan Beaudette [ctb], Benjamin Louis [ctb], Kiri Daust [ctb], David Clifford [ctb]
Maintainer: Pierre Roudier <roudierp at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: clhs citation info
Materials: README NEWS
CRAN checks: clhs results


Reference manual: clhs.pdf
Vignettes: #intro-clhs


Package source: clhs_0.9.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): clhs_0.9.0.tgz, r-oldrel (arm64): clhs_0.9.0.tgz, r-release (x86_64): clhs_0.9.0.tgz, r-oldrel (x86_64): clhs_0.9.0.tgz
Old sources: clhs archive

Reverse dependencies:

Reverse imports: dgpsi, sgsR


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