About the Monte Carlo Sampling Techniques

Isight offers three Monte Carlo sampling techniques.

Descriptive Sampling

In the Descriptive Sampling technique the space defined by each random variable is divided into subsets of equal probability, and the analysis is performed with each subset of each random variable only once (each subset of one random variable is combined with only one subset of each other random variable).

For more information, see Descriptive Sampling.

Simple Random Sampling

The Simple Random Sampling technique generates sample points by generating N uniformly distributed random numbers between 0 and 1 for each random variable and obtaining corresponding values from each random variable distribution.

For more information, see Simple Random Sampling.

Sobol Sampling

Sobol Sampling is a quasi-random sequence of numbers that are more uniformly distributed than both simple random sampling and descriptive sampling. In other words, samples obtained using Sobol's sequences exhibit a probability density function that is closer to the true density function.

For more information, see Sobol Sampling.