Package: clhs 0.9.0

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>).

Authors:Pierre Roudier [aut, cre], Colby Brugnard [ctb], Dylan Beaudette [ctb], Benjamin Louis [ctb], Kiri Daust [ctb], David Clifford [ctb]

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Bug tracker:https://github.com/pierreroudier/clhs/issues

On CRAN:

2 exports 12 stars 2.37 score 48 dependencies 2 dependents 2 mentions 116 scripts 639 downloads

Last updated 2 years agofrom:8d45408d03. Checks:OK: 1 NOTE: 8. Indexed: yes.

Exports:clhssimilarity_buffer

Dependencies:classclassIntcliclustercolorspaceDBIe1071fansifarverggplot2gluegtableisobandKernSmoothlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigplyrproxyR6rasterRColorBrewerRcppRcppArmadilloreshape2rlangs2scalessfspstringistringrterratibbleunitsutf8vctrsviridisLitewithrwk