List of Available Latin Hypercube Design Criteria

The Random class is imported using the following command:

>>> from UQpy.sampling.stratified_sampling.latin_hypercube_criteria.Random import Random

class Random

Method for generating a Latin hypercube design by sampling randomly inside each bin.

The Random class takes a set of samples drawn randomly from within the Latin hypercube bins and performs a random shuffling of them to pair the variables.

The Centered class is imported using the following command:

>>> from UQpy.sampling.stratified_sampling.latin_hypercube_criteria.Centered import Centered

class Centered

Method for generating a Latin hypercube design with samples centered in the bins.

The MaxiMin class is imported using the following command:

>>> from UQpy.sampling.stratified_sampling.latin_hypercube_criteria.MaxiMin import MaxiMin

class MaxiMin(iterations=100, metric=DistanceMetric.EUCLIDEAN)

Method for generating a Latin hypercube design that aims to maximize the minimum sample distance.

Parameters:

• iterations (int) – The number of iteration to run in the search for a maximin design.

• metric (DistanceMetric) – The distance metric to use. Available options are provided in the DistanceMetric enum.

The MinCorrelation class is imported using the following command:

>>> from UQpy.sampling.stratified_sampling.latin_hypercube_criteria.MinCorrelation import MinCorrelation

class MinCorrelation(iterations=100)

Method for generating a Latin hypercube design that aims to minimize spurious correlations.

Parameters:

iterations (int) – The number of iteration to run in the search for a maximin design.