Package: CompExpDes 1.0.7
CompExpDes: Designs for Computer Experimentations
In computer experiments space-filling designs are having great impact. Most popularly used space-filling designs are Uniform designs (UDs), Latin hypercube designs (LHDs) etc. For further references one can see Mckay (1979) <doi:10.1080/00401706.1979.10489755> and Fang (1980) <https://cir.nii.ac.jp/crid/1570291225616774784>. In this package, we have provided algorithms for generate efficient LHDs and UDs. Here, generated LHDs are efficient as they possess lower value of Maxpro measure, Phi_p value and Maximum Absolute Correlation (MAC) value based on the weightage given to each criterion. On the other hand, the produced UDs are having good space-filling property as they always attain the lower bound of Discrete Discrepancy measure. Further, some useful functions added in this package for adding more value to this package.
Authors:
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CompExpDes.pdf |CompExpDes.html✨
CompExpDes/json (API)
# Install 'CompExpDes' in R: |
install.packages('CompExpDes', repos = c('https://ashutoshdalal97.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 days agofrom:67468975fb. Checks:9 OK. Indexed: yes.
Target | Result | Latest binary |
---|---|---|
Doc / Vignettes | OK | Mar 29 2025 |
R-4.5-win | OK | Mar 29 2025 |
R-4.5-mac | OK | Mar 29 2025 |
R-4.5-linux | OK | Mar 29 2025 |
R-4.4-win | OK | Mar 29 2025 |
R-4.4-mac | OK | Mar 29 2025 |
R-4.4-linux | OK | Mar 29 2025 |
R-4.3-win | OK | Mar 29 2025 |
R-4.3-mac | OK | Mar 29 2025 |
Exports:Best_ModelDiscrete_DiscrepancyMACMaxpro_MeasureMeeting_NumberNOLHDsOLHDs_2FPhipMeasureSLHDsUDesigns_IUDesigns_IIUDesigns_IIIwtLHDswtLHDs_prime
Dependencies: