Provides a number of methods for creating and augmenting Latin Hypercube Samples.
Version: | 1.0.1 |
Depends: | R (≥ 3.4.0) |
Imports: | Rcpp |
LinkingTo: | Rcpp |
Suggests: | testthat, DoE.base, knitr, rmarkdown, covr |
Published: | 2019-02-03 |
Author: | Rob Carnell [aut, cre] |
Maintainer: | Rob Carnell <bertcarnell at gmail.com> |
BugReports: | https://github.com/bertcarnell/lhs/issues |
License: | GPL-3 |
URL: | https://github.com/bertcarnell/lhs |
NeedsCompilation: | yes |
Materials: | README ChangeLog |
In views: | Distributions, ExperimentalDesign |
CRAN checks: | lhs results |
Reference manual: | lhs.pdf |
Vignettes: |
An Example of Augmenting a Latin Hypercube Basic Latin hypercube samples and designs with package lhs Latin Hypercube Samples - Questions |
Package source: | lhs_1.0.1.tar.gz |
Windows binaries: | r-devel: lhs_1.0.1.zip, r-release: lhs_1.0.1.zip, r-oldrel: lhs_1.0.1.zip |
OS X binaries: | r-release: lhs_1.0.1.tgz, r-oldrel: lhs_1.0.1.tgz |
Old sources: | lhs archive |
Reverse depends: | acebayes, ATmet, mtk, netgen, tuneRanger |
Reverse imports: | binaryGP, BMhyb, DoE.wrapper, DSAIRM, DynamicGP, EasyABC, GPfit, GPM, grapherator, hydroPSO, inaparc, kernDeepStackNet, LVGP, mcMST, metagen, mlrMBO, optim.functions, ParBayesianOptimization, penalizedSVM, profExtrema, qle, rrepast, spartan, suropt |
Reverse suggests: | BayesianTools, DiceOptim, flacco, GAparsimony, hetGP, IGP, kergp, laGP, maximin, mistat, moko, ParamHelpers, SACOBRA, vdg |
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