R: Optimum Seeded Latin Hypercube Sample

optSeededLHS {lhs} | R Documentation

## Optimum Seeded Latin Hypercube Sample

### Description

Augments an existing Latin Hypercube Sample, adding points to the design, while maintaining the latin properties of the design. This function then uses the columnwise pairwise (CP) algoritm to optimize the design. The original design is not necessarily maintained.

### Usage

    optSeededLHS(seed, m = 0, maxSweeps = 2, eps = 0.1, verbose = FALSE)

### Arguments

`seed` | The number of partitions (simulations or design points)
`m` | The number of additional points to add to the seed matrix `seed`. default value is zero. If m is zero then the seed design is optimized.
`maxSweeps` | The maximum number of times the CP algorithm is applied to all the columns.
`eps` | The optimal stopping criterion
`verbose` | Print informational messages

### Details

Augments an existing Latin Hypercube Sample, adding points to the design, while maintaining the latin properties of the design. This function then uses the CP algoritm to optimize the design. The original design is not necessarily maintained.

### Value

An `n` by `k` Latin Hypercube Sample matrix with values uniformly distributed on [0,1]

### References

Stein, M. (1987) Large Sample Properties of Simulations Using Latin Hypercube Sampling. Technometrics. 29, 143–151.

### See Also

[randomLHS()], [geneticLHS()], [improvedLHS()], [maximinLHS()], and [optimumLHS()] to generate Latin Hypercube Samples. [optAugmentLHS()] and [augmentLHS()] to modify and augment existing designs.

### Examples

      set.seed(1234)
      a <- randomLHS(4,3)
      b <- optSeededLHS(a, 2, 2, .1)

[Package lhs version 1.1.3 Index]