Designing experimental plans that involve both discrete and continuous factors with general parametric statistical models using the 'ForLion' algorithm and 'EW ForLion' algorithm. The algorithms will search for locally optimal designs and EW optimal designs under the D-criterion. Reference: Huang, Y., Li, K., Mandal, A., & Yang, J., (2024)<doi:10.1007/s11222-024-10465-x>.
Version: | 0.1.0 |
Imports: | psych, stats, cubature |
Suggests: | knitr, rmarkdown |
Published: | 2025-02-11 |
DOI: | 10.32614/CRAN.package.ForLion |
Author: | Yifei Huang [aut], Siting Lin [aut, cre], Jie Yang [aut] |
Maintainer: | Siting Lin <slin95 at uic.edu> |
License: | MIT + file LICENSE |
NeedsCompilation: | no |
Materials: | README |
CRAN checks: | ForLion results |
Reference manual: | ForLion.pdf |
Vignettes: |
Introduction to ForLion package (source, R code) |
Package source: | ForLion_0.1.0.tar.gz |
Windows binaries: | r-devel: ForLion_0.1.0.zip, r-release: ForLion_0.1.0.zip, r-oldrel: ForLion_0.1.0.zip |
macOS binaries: | r-devel (arm64): ForLion_0.1.0.tgz, r-release (arm64): ForLion_0.1.0.tgz, r-oldrel (arm64): ForLion_0.1.0.tgz, r-devel (x86_64): ForLion_0.1.0.tgz, r-release (x86_64): ForLion_0.1.0.tgz, r-oldrel (x86_64): ForLion_0.1.0.tgz |
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