Simple Random
The conventional approach of sampling is commonly called Simple Random or Monte Carlo. In Simple Random sampling, a pseudo-random number generator is used for generating random numbers from 0 to 1.
Usability Characteristics
- The statistical measures (such as mean or standard deviation) of a random sample group requires large numbers of runs to converge the given probability distribution’s statistical measures.
- A correlation structure can be specified to reflect the correlation existing between random variables. Applying a correlation structure can be costly for a large number of input variables.
Settings
Parameter | Default | Range | Description |
---|---|---|---|
Number of Runs | 100 | > 0 | Number of new designs to be evaluated. |
Random Seed | 1 | Integer 0 to 10000 |
Controlling repeatability of
runs depending on the way the sequence of random numbers is
generated.
|
Apply User Correlations | On | Off or On | Apply user specified correlations on the data. |