Projection Pursuit Multivariate Sampling of Parameter Uncertainty by Oktay Erten, Fábio P. L. Pereira, Clayton V. Deutsch

“…Five sampling techniques including Monte Carlo simulation, classic Latin hypercube sampling, maximin Latin hypercube sampling, Latin hypercube sampling with multidimensional uniformity, and projection pursuit multivariate transform are employed in the simulation studies, considering cases where the sample sizes <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>(</mo><mi>n</mi><mo>)</mo></mrow></semantics></math></inline-formula> are small (i.e., <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>10</mn><mo>≤</mo><mi>n</mi><mo>≤</mo><mn>100</mn></mrow></semantics></math></inline-formula>), medium (i.e., <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>100</mn><mo><</mo><mi>n</mi><mo>≤</mo><mn>1000</mn></mrow></semantics></math></inline-formula>), and large (i.e., 1000 < <i>n</i>≤ 10,000). …”
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