lhs: Random Latin Hypercube Sampling

In rpouillot/mc2d: Tools for Two-Dimensional Monte-Carlo Simulations

Random Latin Hypercube Sampling

Description

Creates a Latin Hypercube Sample (LHS) of the specified distribution.

Usage

lhs(distr="runif", nsv=ndvar(), nsu=ndunc(), nvariates=1, ...)

Arguments

distr	The function for generating random sample or its name. If ‘⁠distr⁠’ is "rdist", the function "qdist" must be the quantile function of this distribution with argument ‘⁠p⁠’ as a vector of probabilities, as all univariates distributions of the ‘⁠stat⁠’ library.
nsv	The number of rows of the final matrix.
nsu	The number of columns of the final matrix
nvariates	The number of variates
...	All arguments to be passed to ‘⁠distr⁠’ except the size of the sample.

Value

A ‘⁠nsv x nsu⁠’ matrix of random variates.

Note

The resulting lhs is in fact a latin hypersquare sampling: the lhs is provided only in the first 2 dimensions.

It is not possible to send truncated distribution with rtrunc. Use mcstoc for this purpose, with ‘⁠lhs=TRUE⁠’ and ‘⁠rtrunc=TRUE⁠’.

The ... arguments will be recycled.

Author(s)

adapted from a code of Rob Carnell (library ‘⁠lhs⁠’)

See Also

mcstoc

Examples

ceiling(lhs(runif, nsu=10, nsv=10)*10)

rpouillot/mc2d documentation built on June 7, 2024, 12:11 a.m.