Tutorial 15 - Adding Probabilistic Properties to the Case


In this video...
  • Adding sampled parameters with triangular distribution
  • Calculating a probabilistic case
  • Plotting results from a probabilistic case
Key terms...
  • 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.


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