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Table 2 Considered approximate probabilistic model checking approaches

From: Automatic validation of computational models using pseudo-3D spatio-temporal model checking

  Frequentist Bayesian
Estimate Chernoff-Hoeffding  
  bounds [49] Mean and variance [50]
Hypothesis testing Statistical [51] Statistical [17]
  black-box [52],[53]  
  1. Bayesian methods consider prior knowledge about the parameters and variables in the model when deciding if a logic property holds. Conversely frequentist approaches assume no prior knowledge is available. All methods except probabilistic black-box take as input a user-defined upper bound on the approximation error. They request additional model executions until the result is sufficiently accurate. Probabilistic black-box model checking takes a fixed number of model simulations as input and computes a p-value as the confidence measure of the result.