![]() ![]() This set of Nn-tuples is the Latin hypercube sample. These N pairs are combined in a random manner with the N values of x 3 to form Nn-triplets, and so on, until a set of Nn-tuples is formed. The N values thus obtained for x 1 are paired in a random manner with the N values of x 2. One value from each interval is selected at random with respect to the probability density in the interval. The range of each variable is partitioned into N non-overlapping intervals on the basis of equal probability size 1 / N. As originally described, in the following manner, LHS operates to generate a sample size N from the x variables x 1, x 2, x 3. Moreover, the sample generation for correlated components with Gaussian distribution can be easily achieved. We will only consider the case where the components of x are independent or can be transformed into an independent base. The sampling region is partitioned into a specific manner by dividing the range of each component of x. The Latin Hypercube Sampling (LHS) is a type of stratified Monte Carlo (MC). ![]()
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