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>).

Install the latest version of this package by entering the following in R:
install.packages("clhs")
AuthorPierre Roudier
Date of publication2016-10-14 00:10:02
MaintainerPierre Roudier <roudierp@landcareresearch.co.nz>
LicenseGPL (>= 2)
Version0.5-6

View on CRAN

Functions

clhs Man page
clhs.data.frame Man page
clhs,data.frame-method Man page
clhs-package Man page
clhs.Raster Man page
clhs,Raster-method Man page
cLHS_result Man page
clhs.SpatialPointsDataFrame Man page
clhs,SpatialPointsDataFrame-method Man page
plot.cLHS_result Man page

Files

inst
inst/CITATION
inst/doc
inst/doc/vignette.Rnw
inst/doc/vignette.pdf
inst/doc/vignette.R
NAMESPACE
NEWS
R
R/utils.R R/plot.R R/clhs.R R/clhs-internal.R R/clhs-raster.R R/clhs-sp.R R/AAAA.R
vignettes
vignettes/vignette.Rnw
README.md
MD5
build
build/vignette.rds
DESCRIPTION
man
man/clhs-package.Rd man/cLHS_result.Rd man/clhs.Rd man/plot.cLHS_result.Rd
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Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.