user:algorithm:lhs [Promethee]

Latin Hypercube Sampling


Draws a Latin Hypercube Sample from a set of uniform distributions for use in creating a Latin Hypercube Design. The following parameters are available for fine tuning of the algorithm:
  • Random LHS:
    • “Number of experiments”
  • OptimumLHS:
    • “Number of experiments”
    • “Maximum applications of the CP algorithm”
    • “Optimal stopping criterion”
  • Improved LHS:
    • “Number of experiments”
    • “Number of candidate points used in the search”
  • Maximin LHS
    • “Number of experiments”
    • “Number of candidate points used in the search”
The resulting analysis is a simple “pairs” plot:



  • Stocki, R. (2005) A method to improve design reliability using optimal Latin hypercube sampling _Computer Assisted Mechanics and Engineering Sciences_ *12*, 87-105.
  • Beachkofski, B., Grandhi, R. (2002) Improved Distributed Hypercube Sampling _American Institute of Aeronautics and Astronautics Paper_ *1274*. This function is based on the MATLAB program written by John Burkardt and modified 16 Feb 2005
  • Stein, M. (1987) Large Sample Properties of Simulations Using Latin Hypercube Sampling. _Technometrics_. *29*, 143-151.


This LHS algorithms are wrapped from the [R] package LHS .


  • copy in “Promethee_Install_Path/plugins/doe directory”,
  • restart Promethee GUI.
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