Description Usage Arguments Details Value Author(s) See Also Examples
Draws a Latin Hypercube Sample from a set of uniform distributions in the transformed parameter space,in creating a Latin Hypercube Design. This function uses the Columnwise Pairwise (CP) algorithm to generate an optimal design with respect to the S optimality criterion, as implemented in lhs-package.
1 |
p |
vector of model parameters |
psel |
|
plo |
|
pup |
|
trans.L |
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Npop |
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Produces and optimum latin hypercube sample from a bounded uniform distribution.
n
draws of k
parameters in an n x k
Latin Hypercube Sample matrix with values uniformly distributed on user specified bounds.
Tobias KD Weber , tobias.weber@uni-hohenheim.de
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | # Example based on soil hydraulic property model parameters of shpmodel = "01110" parameters
parL <- list("p" = c("thr"= 0.05, "ths" = 0.45, "alf1" = 0.01, "n" = 2, "Ks" = 100, "tau" = .5),
"psel" = c(1, 1, 0, 1, 1, 1),
"plo" = c(0.001 , 0.2, 0.001, 1.1, 1, -2),
"pup" = c(0.3, 0.95, 1, 10, 1e4, 10)
)
# rules for the parameter transformation
ptransfit<- c(function(x)x, function(x)x,log10,
function(x)log10(x-1),log10 , function(x)x)
# get latin hypercube sample.
test.inipop <- inipopFun(parL$p, parL$psel,
parL$plo, parL$pup, ptransfit, Npop = 20)
# plot the latin hypercube
pairs(test.inipop)
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