Huong Le
@huong-le.bsky.social
Geostatistics, Geospatial Analyst, Data Scientist, Climate Change Analyst, GIS-Remote sensing Analyst, Machine Learning, Sampling design, Copulas
Reposted by Huong Le
🚀 Excited to share our new R package aclhs — now on CRAN! @huong-le.bsky.social #VargasLab
It implements autocorrelated conditioned Latin hypercube sampling (acLHS), an improvement over the traditional LHS for data and models with spatial or temporal dependence
🔗 cran.r-project.org/web/packages...
It implements autocorrelated conditioned Latin hypercube sampling (acLHS), an improvement over the traditional LHS for data and models with spatial or temporal dependence
🔗 cran.r-project.org/web/packages...
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 Hyp...
cran.r-project.org
November 12, 2025 at 2:13 AM
🚀 Excited to share our new R package aclhs — now on CRAN! @huong-le.bsky.social #VargasLab
It implements autocorrelated conditioned Latin hypercube sampling (acLHS), an improvement over the traditional LHS for data and models with spatial or temporal dependence
🔗 cran.r-project.org/web/packages...
It implements autocorrelated conditioned Latin hypercube sampling (acLHS), an improvement over the traditional LHS for data and models with spatial or temporal dependence
🔗 cran.r-project.org/web/packages...