lhs {tgp} | R Documentation |
Draw a (random) Latin Hypercube (LH) sample of size n
from in
the region outlined by the provided rectangle
lhs(n, rect, shape=NULL, mode=NULL)
n |
Size of the LH sample |
rect |
Rectangle describing the domain from which the LH sample
is to be taken. The rectangle should be a matrix or
data.frame with ncol(rect) = 2 , and number of rows equal to the
dimension of the domain. For 1-d data, a vector of length 2
is allowed |
shape |
Optional vector of shape parameters for the Beta distribution.
Vector of length equal to the dimension of the domain, with elements > 1.
If this is specified, the LH sample is proportional to a joint pdf formed by
independent Beta distributions in each dimension of the domain,
scaled and shifted to have support defined by rect .
Only concave Beta distributions with shape > 1 are supported. |
mode |
Optional vector of mode values for the Beta distribution.
Vector of length equal to the dimension of the domain, with elements within
the support defined by rect . If shape is specified,
but this is not, then the scaled Beta distributions will be symmetric |
The output is a matrix
with n
rows and
nrow(rect)
columns. Each of the n
rows represents
a sample point.
The domain bounds specified by the rows of rect
can
be specified backwards with no change in effect.
Robert B. Gramacy, rbgramacy@ams.ucsc.edu, and Matt Taddy, taddy@ams.ucsc.edu
McKay, M. D., W. J. Conover and R. J. Beckman. (1979). A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code, Technometrics 21: (pp. 239–245).
# get and plot a 2-d LH design s1 <- lhs(10, rbind(c(-2,3), c(0.5, 0.8))) plot(s1) # plot a grid to show that there is one sample # in each grid location abline(v=seq(-2,3,length=11), lty=2, col=3) abline(h=seq(0.5,0.8,length=11), lty=2, col=3)