Latinhyper {FME} | R Documentation |
Generates random parameter sets using a latin hypercube sampling algorithm.
Latinhyper(parRange, num)
parRange |
the range (min, max) of the parameters, a matrix or a data.frame with one row for each parameter, and two columns with the minimum (1st) and maximum (2nd) column. |
num |
the number of random parameter sets to generate. |
In the latin hypercube sampling, the space for each parameter is subdivided
into num
equally-sized segments and one parameter value in each of
the segments drawn randomly.
a matrix with one row for each generated parameter set, and one column per parameter.
The latin hypercube distributed parameter sets give better coverage in
parameter space than the uniform random design (Unif
).
It is a reasonable choice in case the number of parameter sets is limited.
Karline Soetaert <k.soetaert@nioo.knaw.nl>
Press, W. H., Teukolsky, S. A., Vetterling, W. T. and Flannery, B. P. (2007) Numerical Recipes in C. Cambridge University Press.
Norm
for (multi)normally distributed random parameter sets.
Unif
for uniformly distributed random parameter sets.
Grid
to generate random parameter sets arranged on a regular
grid
## 4 parameters parRange <- data.frame(min = c(0, 1, 2, 3), max = c(10, 9, 8, 7)) rownames(parRange) <- c("par1", "par2", "par3", "par4") ## Latin hypercube pairs(Latinhyper(parRange, 100), main = "Latin hypercube")