Random
In this method a sample (x1, x2, …, xm ), of the desired dimension, m, is generated from the joint distribution of the input variables or, when these are independent, from their marginal distributions. Random sampling is also referred to as pseudo random, as the random numbers are machine-generated with deterministic process and not random stricto sensu. From the statistical point of view random sampling has advantages, as it produces unbiased estimates of the mean and the variance of the output variables. In this model the number of model executions should not be smaller than 1.5 the number of variables; possibly a much larger value (e.g. 10 times the number of variables) should be used.
IMPORTANT: Random method can be used independently by the factors set selected