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SFDesign (version 0.1.3)

Space-Filling Designs

Description

Construct various types of space-filling designs, including Latin hypercube designs, clustering-based designs, maximin designs, maximum projection designs, and uniform designs (Joseph 2016 ). It also offers the option to optimize designs based on user-defined criteria. This work is supported by U.S. National Science Foundation grant DMS-2310637.

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Version

Install

install.packages('SFDesign')

Monthly Downloads

142

Version

0.1.3

License

GPL (>= 2)

Maintainer

Shangkun Wang

Last Published

September 30th, 2025

Functions in SFDesign (0.1.3)

uniform.optim

Optimize a design based on the wrap-around discrepancy
uniformLHD

Generate a uniform Latin-hypercube design (LHD)
maximin.remove

Sequentially remove design points from a design while maintaining low reciprocal distance criterion as possible
cluster.error

Clustering error
SFDesign-package

Space-Filling designs
maximin.crit

Maximin criterion
clustering.design

Designs generated by clustering algorithms
maximin.optim

Optimize a design based on maximin or reciprocal distance criterion
maximin.augment

Augment a design by adding new design points that minimize the reciprocal distance criterion greedily
full.factorial

Full factorial design
customLHD

Generate a Latin-hypercube design (LHD) based on a custom criterion
continuous.optim

Continuous optimization of a design
maximinLHD

Generate a maximin Latin-hypercube design (LHD)
randomLHD

Random Latin hypercube design
maxproLHD

Generate a MaxPro Latin-hypercube design
uniform.crit

Uniform criterion
maxpro.optim

Optimize a design based on the maximum projection criterion
maxpro.remove

Sequentially remove design points from a design while maintaining low maximum projection criterion as possible
uniform.discrete

Generate a uniform design for discrete factors with different number of levels
maxpro.crit

Maximum projection (MaxPro) criterion