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1. STRATIFIED SAMPLING LATIN HYPERCUBE SAMPLING MANUAL
2. STRATIFIED SAMPLING LATIN HYPERCUBE SAMPLING SOFTWARE
3. STRATIFIED SAMPLING LATIN HYPERCUBE SAMPLING WINDOWS

However, the high cost in constructing them limits their use. Optimal Latin hypercube designs are frequently used and have been shown to have good space-filling and projective properties. The accuracy of metamodels is directly related to the experimental designs used. Metamodels have been widely used in engineering design to facilitate analysis and optimization of complex systems that involve computationally expensive simulation programs. The procedure is intended for use in conjunction with uncertainty and sensitivity analysis of computationally demanding models in which it is important to make efficient use of a necessarily limited number ofmore » model evaluations.« lessĪ Novel Latin Hypercube Algorithm via Translational Propagation The extension procedure starts with an LHS of size m and associated rank correlation matrix C and constructs a new LHS of size 2m that contains the elements of the original LHS and has a rank correlation matrix that is close to the original rank correlation matrix C.

PhD.Ī procedure for extending the size of a Latin hypercube sample (LHS) with rank correlated variables is described and illustrated. Hora, Stephen Curtis Helton, Jon Craig Sallaberry, Cedric J.

STRATIFIED SAMPLING LATIN HYPERCUBE SAMPLING MANUAL

This manual covers the use of the LHS code as a library and in the standalone mode under UNIX.« lessĮxtension of latin hypercube samples with correlated variables. However, some modifications were made to customize it for a UNIX environment and as a librarymore » that is called from the DAKOTA environment.

STRATIFIED SAMPLING LATIN HYPERCUBE SAMPLING WINDOWS

The underlying code in the UNIX Library/Standalone version of LHS is almost identical to the updated Windows version of LHS released in 1998 (SAND98-0210). This manual covers the use of the LHS code in a UNIX environment, run either as a standalone program or as a callable library. This version runs on Linux or UNIX platforms.

STRATIFIED SAMPLING LATIN HYPERCUBE SAMPLING SOFTWARE

This software has been developed to generate Latin hypercube multivariate samples. This document is a reference guide for the UNIX Library/Standalone version of the Latin Hypercube Sampling Software. If this is done repeatedly, with many input samples drawn, one can build up a distribution of the output as well as examine correlations between input and output variables.« lessĪ user's guide to Sandia's latin hypercube sampling software : LHS UNIX library/standalone version. Many simulation codes have input parameters that are uncertain and can be specified by a distribution, To perform uncertainty analysis and sensitivity analysis, random values are drawn from the input parameter distributions, and the simulation is run with these values to obtain output values.

In some cases, the pairing is restricted to obtain specified correlations amongst the input variables. A sample is selected at random with respect to the probability density in each interval, If multiple variables are sampled simultaneously, then values obtained for each are paired in a random manner with the n values of the other variables. Inmore » LHS, the range of each variable is divided into non-overlapping intervals on the basis of equal probability. LHS is a constrained Monte Carlo sampling scheme. LHS UNIX Library/Standalone uses the Latin Hypercube Sampling method (LHS) to generate samples. The LHS samples can be generated either as a callable library (e.g., from within the DAKOTA software framework) or as a standalone capability. Multiple distributions can be sampled simultaneously, with user-specified correlations amongst the input distributions, LHS UNIX Library/ Standalone provides a way to generate multi-variate samples. It performs the sampling by a stratified sampling method called Latin Hypercube Sampling (LHS). The LHS UNIX Library/Standalone software provides the capability to draw random samples from over 30 distribution types.

This paper develops asymptotically valid confidence intervals for quantiles that are estimated via simulation using LHS.Latin Hypercube Sampling (LHS) UNIX Library/Standalone This paper develops asymptotically valid confidence intervals for quantiles that are estimated via simulation using LHS.ĪB - Latin hypercube sampling (LHS) is a variance-reduction technique (VRT) that can be thought of as an extension of stratified sampling in multiple dimensions. N2 - Latin hypercube sampling (LHS) is a variance-reduction technique (VRT) that can be thought of as an extension of stratified sampling in multiple dimensions. T1 - Confidence intervals for quantiles when applying latin hypercube sampling