Conditioned Latin hypercube sampling, as published by Minasny and McBratney (2006). 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).
|Depends:||R (≥ 2.14.0)|
|Imports:||utils, methods, grid, ggplot2, sp, raster, reshape2, plyr, scales|
|Maintainer:||Pierre Roudier <roudierp at landcareresearch.co.nz>|
|License:||GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]|
|Citation:||clhs citation info|
|CRAN checks:||clhs results|
Introduction to conditioned Latin hypercube sampling with the clhs package
|Windows binaries:||r-devel: clhs_0.5-5.zip, r-release: clhs_0.5-5.zip, r-oldrel: clhs_0.5-5.zip|
|OS X Mavericks binaries:||r-release: clhs_0.5-5.tgz, r-oldrel: clhs_0.5-5.tgz|
|Old sources:||clhs archive|
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