In this video...
- Adding sampled parameters with triangular distribution
- Calculating a probabilistic case
- Plotting results from a probabilistic case
- Stochastic parameters are parameters defined using a Probability Density Function (PDF), rather than a discrete value.
- Deterministic Cases in AMBER are cases in which none of the parameters are defined using PDFs.
- Probabilistic Cases in AMBER are cases in which one or more parameters is sampled
- Full Sampling allows variation over all sampled parameters
- Partial Sampling allows variation over some sampled parameters, and fixes other at their best estimate values
- Best Estimates Sampling fixes all sampled parameters to their best estimates, making the calculation deterministic
- Latin Hypercube Sampling generates a sample set that optimises the coverage when a number of parameters are sampled together
- Seeds are used in probabilistic calculations to initiate the random number generator that determines the sampled values.
This video covers section 9.1 of the User Guide.