Nguyen's Orthogonal Latin Hypercube Designs
Generate the Orthogonal Latin Hypercube (OLH) designs proposed by Nguyen in 2008. These OLHs have a latin structure, an orthogonality between the main terms and the interactions (+ squares) and low correlations between the interactions (+ squares). Very larges matrices can be obtained as the number of input variables and hence the number of lines is unconstrained. When the number of input variables is a power of 2, OLHs have d columns and n = 2d + 1 lines (experiments). A vertical truncature is applied when the number of input variables is not a power of 2. Various normalizations can be applied.
olhDesign(dimension, range = c(0, 1))
dimension |
number of input variables |
range |
the scale (min and max) of the inputs. Ranges (0, 0) and (1, 1) are special cases and call integer ranges (-d, d) and (0, 2d). See the examples |
A list with components:
n |
the number of lines/experiments |
dimension |
the number of columns/input variables |
design |
the design of experiments |
N.K. Nguyen for the algorithm. P. Kiener for the recursive R code.
Nguyen N.K. (2008) A new class of orthogonal Latinhypercubes, Statistics and Applications, Volume 6, issues 1 and 2, pp.119-123.
Cioppa's and De Rainville's NOLH designs: nolhDesign, nolhdrDesign.
## Classical normalizations olhDesign(4, range = c(0, 0)) olhDesign(4, range = c(1, 1)) olhDesign(4, range = c(0, 1)) olhDesign(4, range = c(-1, 1)) ## Change the dimnames, adjust to range (-10, 10) and round to 2 digits xDRDN(olhDesign(4), letter = "T", dgts = 2, range = c(-10, 10)) ## A list of designs lapply(1:5, function(n) olhDesign(n, range = c(-1, 1))$design)
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