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: 0.8.1
Depends: R (≥ 2.14.0)
Imports: utils, methods, grid, ggplot2, sp, sf, raster, reshape2, plyr, cluster
Suggests: knitr, rmarkdown, testthat
Published: 2021-05-10
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 landcareresearch.co.nz>
BugReports: https://github.com/pierreroudier/clhs/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/pierreroudier/clhs/
NeedsCompilation: no
Citation: clhs citation info
Materials: README NEWS
CRAN checks: clhs results

Downloads:

Reference manual: clhs.pdf
Vignettes: #intro-clhs
Package source: clhs_0.8.1.tar.gz
Windows binaries: r-devel: clhs_0.8.1.zip, r-release: clhs_0.8.1.zip, r-oldrel: clhs_0.8.1.zip
macOS binaries: r-release (arm64): clhs_0.8.1.tgz, r-release (x86_64): clhs_0.8.1.tgz, r-oldrel: clhs_0.8.1.tgz
Old sources: clhs archive

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