![]() Matlab has a special lhsdesign function to generate a Latin cubic sampling probability matrix. The greater the value of N, the better the resulting data. Each of these n numbers is the probability of each random sample, and the value of the random distribution is generated according to the inverse function of the probability distribution function. ![]() The order of n random numbers is disturbed.ģ. ![]() divided into n equal parts, each small interval in accordance with uniform distribution randomly generated a number.Ģ. Latin cubic sampling must first explicitly generate the number of samples N, Latin cubic sampling of the steps:ġ. It can be seen that most of the data in the simple random sampling are in the middle, while the Latin cubic sampling is evenly generated in each small interval. The following diagram illustrates the difference between the two: When a random sample is generated, there is a problem of excessive data aggregation, which is solved by the Latin hypercube sampling.
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