aclhs: Autocorrelated Conditioned Latin Hypercube Sampling
Implementation of the autocorrelated conditioned Latin Hypercube Sampling (acLHS) algorithm for 1D (time-series) and 2D (spatial) data. The acLHS algorithm is an extension of the conditioned Latin Hypercube Sampling (cLHS) algorithm that allows sampled data to have similar correlative and statistical features of the original data. Only a properly formatted dataframe needs to be provided to yield subsample indices from the primary function. For more details about the cLHS algorithm, see Minasny and McBratney (2006), <doi:10.1016/j.cageo.2005.12.009>. For acLHS, see Le and Vargas (2024) <doi:10.1016/j.cageo.2024.105539>.
| Version: | 1.0.1 |
| Depends: | R (≥ 3.5) |
| Imports: | DEoptim (≥ 2.2.8),geoR (≥ 1.9.6), graphics (≥ 4.5.1), stats (≥ 4.5.1), utils (≥ 4.5.1) |
| Suggests: | testthat (≥ 3.0.0) |
| Published: | 2025-11-05 |
| DOI: | 10.32614/CRAN.package.aclhs |
| Author: | Van Huong Le [aut, ctb], Rodrigo Vargas [aut], Gabriel Laboy [ctb, cre] |
| Maintainer: | Gabriel Laboy <glaboy1 at asu.edu> |
| BugReports: | https://github.com/vargaslab/acLHS/issues |
| License: | MIT + fileLICENSE |
| URL: | https://github.com/vargaslab/acLHS |
| NeedsCompilation: | no |
| Citation: | aclhs citation info |
| CRAN checks: | aclhs results |
Documentation:
| Reference manual: | aclhs.html ,aclhs.pdf |
Downloads:
| Package source: | aclhs_1.0.1.tar.gz |
| Windows binaries: | r-devel:aclhs_1.0.1.zip, r-release:aclhs_1.0.1.zip, r-oldrel:not available |
| macOS binaries: | r-release (arm64):aclhs_1.0.1.tgz, r-oldrel (arm64): not available, r-release (x86_64):aclhs_1.0.1.tgz, r-oldrel (x86_64): not available |
Linking:
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