|
Frequentist
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Bayesian
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Estimate
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Chernoff-Hoeffding
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|
bounds [49]
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Mean and variance [50]
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Hypothesis testing
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Statistical [51]
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Statistical [17]
|
|
Probabilistic
| |
|
black-box [52],[53]
| |
- 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.