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aclhs

Autocorrelated Conditioned Latin Hypercube Sampling

v1.0.1 · Nov 5, 2025 · MIT + file LICENSE

Description

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>.

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package dependencies

Packages required and available but unsuitable versions:
  'graphics', 'stats', 'utils'

See section ‘The DESCRIPTION file’ in the ‘Writing R Extensions’
manual.

Check History

ERROR 10 OK · 0 NOTE · 0 WARNING · 4 ERROR · 0 FAILURE Mar 10, 2026
ERROR r-release-macos-arm64

package dependencies

Packages required and available but unsuitable versions:
  'graphics', 'stats', 'utils'

See section ‘The DESCRIPTION file’ in the ‘Writing R Extensions’
manual.
ERROR r-oldrel-macos-arm64

package dependencies

Packages required and available but unsuitable versions:
  'graphics', 'stats', 'utils'

See section ‘The DESCRIPTION file’ in the ‘Writing R Extensions’
manual.
ERROR r-oldrel-macos-x86_64

package dependencies

Packages required and available but unsuitable versions:
  'graphics', 'stats', 'utils'

See section ‘The DESCRIPTION file’ in the ‘Writing R Extensions’
manual.
ERROR r-oldrel-windows-x86_64

package dependencies

Packages required and available but unsuitable versions:
  'graphics', 'stats', 'utils'

See section 'The DESCRIPTION file' in the 'Writing R Extensions'
manual.

Dependency Network

Dependencies Reverse dependencies DEoptim geoR aclhs

Version History

1 tracked
new 1.0.1 Mar 10, 2026

R Observatory began tracking this package on Mar 10, 2026; it first appeared on CRAN Nov 5, 2025. Releases before tracking aren’t shown.