Different ways to quantify uncertainty
There are several different approaches to quantify uncertainty, each with its own strengths and limitations. Here are a few examples:
- Statistical methods: Statistical methods are widely used for UQ and involve using probability distributions to model the uncertainty in data and predictions. These methods are widely used in fields such as finance, engineering, and physics and involve tools such as confidence intervals, regression analysis, Monte Carlo simulations and hypothesis testing.
- Bayesian methods: Bayesian methods involve using prior knowledge and data to update our beliefs about the uncertainty in predictions. These methods are widely used in machine learning, natural language processing, and image processing. Bayesian tools include Bayesian inference – statistical methods to update beliefs about the uncertainty of predictions based on new data – and Bayesian networks – graphical models that represent probability...
