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:
clhs_0.9.0.tar.gz
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clhs_0.9.0.tgz(r-4.4-x86_64)clhs_0.9.0.tgz(r-4.4-arm64)clhs_0.9.0.tgz(r-4.3-x86_64)clhs_0.9.0.tgz(r-4.3-arm64)
clhs_0.9.0.tar.gz(r-4.5-noble)clhs_0.9.0.tar.gz(r-4.4-noble)
clhs_0.9.0.tgz(r-4.4-emscripten)clhs_0.9.0.tgz(r-4.3-emscripten)
clhs.pdf |clhs.html✨
clhs/json (API)
NEWS
| # Install 'clhs' in R: |
| install.packages('clhs', repos = c('https://pierreroudier.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/pierreroudier/clhs/issues
Last updated 3 years agofrom:8d45408d03. Checks:OK: 1 NOTE: 8. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 26 2024 |
| R-4.5-win-x86_64 | NOTE | Oct 26 2024 |
| R-4.5-linux-x86_64 | NOTE | Oct 26 2024 |
| R-4.4-win-x86_64 | NOTE | Oct 26 2024 |
| R-4.4-mac-x86_64 | NOTE | Oct 26 2024 |
| R-4.4-mac-aarch64 | NOTE | Oct 26 2024 |
| R-4.3-win-x86_64 | NOTE | Oct 26 2024 |
| R-4.3-mac-x86_64 | NOTE | Oct 26 2024 |
| R-4.3-mac-aarch64 | NOTE | Oct 26 2024 |
Exports:clhssimilarity_buffer
Dependencies:classclassIntcliclustercolorspaceDBIe1071fansifarverggplot2gluegtableisobandKernSmoothlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigplyrproxyR6rasterRColorBrewerRcppRcppArmadilloreshape2rlangs2scalessfspstringistringrterratibbleunitsutf8vctrsviridisLitewithrwk
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Conditioned Latin Hypercube Sampling | clhs-package |
| Conditioned Latin Hypercube Sampling | clhs clhs.data.frame clhs.Raster clhs.sf clhs.SpatialPointsDataFrame |
| Conditioned Latin Hypercube Sampling result | cLHS_result |
| This is the internal Cpp function used to run the metropolis hasting algorithm if use.cpp = T. In general, it shouldn't be used as a stand alone function, because some preprocessing is done in R | CppLHS |
| Plot cLHS results | plot.cLHS_result |
| Gower similarity analysis | similarity_buffer |
