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/b12728-46>).

Version: 0.6-0
Depends: R (≥ 2.14.0)
Imports: utils, methods, grid, ggplot2, sp, raster, reshape2, plyr, scales, cluster
Suggests: knitr, rmarkdown, testthat
Published: 2018-04-13
Author: Pierre Roudier [aut, cre], Colby Brugnard [ctb], Dylan Beaudette [ctb]
Maintainer: Pierre Roudier <roudierp at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: clhs citation info
Materials: README NEWS
CRAN checks: clhs results


Reference manual: clhs.pdf
Vignettes: #intro-clhs
Package source: clhs_0.6-0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: clhs_0.6-0.tgz, r-oldrel: clhs_0.6-0.tgz
Old sources: clhs archive


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