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clhs  

Conditioned Latin Hypercube Sampling
View on CRAN: Click here


Download and install clhs package within the R console
Install from CRAN:
install.packages("clhs")

Install from Github:
library("remotes")
install_github("cran/clhs")

Install by package version:
library("remotes")
install_version("clhs", "0.9.2")



Attach the package and use:
library("clhs")
Maintained by
Pierre Roudier
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2012-01-13
Latest Update: 2021-10-14
Description:
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, ).
How to cite:
Pierre Roudier (2012). clhs: Conditioned Latin Hypercube Sampling. R package version 0.9.2, https://cran.r-project.org/web/packages/clhs. Accessed 26 Jun. 2026.
Previous versions and publish date:
0.4-3 (2012-01-13 09:05), 0.5-0 (2012-06-07 09:08), 0.5-1 (2012-09-10 11:37), 0.5-4 (2014-09-18 09:56), 0.5-5 (2015-12-18 06:43), 0.5-6 (2016-10-14 00:10), 0.5-7 (2017-09-12 01:22), 0.6-0 (2018-04-13 05:18), 0.7-0 (2018-10-11 01:00), 0.7-2 (2019-05-07 00:30), 0.7-3 (2020-04-15 13:30), 0.8.1 (2021-05-10 06:32), 0.9.0 (2021-10-14 06:30)
Other packages that cited clhs R package
View clhs citation profile
Other R packages that clhs depends, imports, suggests or enhances
Complete documentation for clhs
Functions, R codes and Examples using the clhs R package
Some associated functions: CppLHS . cLHS_result . clhs-package . clhs . plot.cLHS_result . similarity_buffer . 
Some associated R codes: RcppExports.R . clhs-data.frame.R . clhs-internal.R . clhs-package.R . clhs-raster.R . clhs-sf.R . clhs-sp.R . clhs.R . plot.R . similarity.R . utils.R .  Full clhs package functions and examples
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