Sampling Methods
The Sampling Method determines how the statistical input distributions will be sampled and is configured through the Project Settings Probability Settings tab.
To open the tab:
- Open the
Project Settings dialog.
- Select the Probability Settings tab.
Two Sampling Methods are available in RocFall – Monte-Carlo or Latin-Hypercube sampling.
Monte-Carlo Method
The Monte-Carlo sampling technique uses random numbers to sample from the input data probability distributions. Monte-Carlo techniques are commonly applied to a wide variety of problems involving random behaviour in geotechnical engineering.
![Monte Carlo sampling of Normal distribution (1000 samples)](/assets/help/rocfall/images/images/pictures/fig_sampling_monte.gif)
Latin-Hypercube Method
The Latin-Hypercube sampling technique gives comparable results to the Monte-Carlo technique but with fewer samples. The method is based upon "stratified" sampling with random selection within each stratum. This results in a smoother sampling of the probability distributions. Typically, an analysis using 1000 samples obtained by the Latin-Hypercube technique will produce comparable results to an analysis of 5000 samples using the Monte-Carlo method.
![Latin Hypercube sampling of Normal distribution (1000 samples)](/assets/help/rocfall/images/images/pictures/fig_sampling_latin.gif)