bayesian
- Adjective:
- Relating to statistical methods based on Bayes' theorem: The term "Bayesian" describes an approach to probability and statistics that interprets probability as a measure of belief or certainty, which can be updated as new evidence is acquired, using the mathematical framework of Bayes' theorem.
- Adjective:
- The researcher used a Bayesian approach to update the model's predictions with the new data.
- Bayesian inference is a powerful tool for dealing with uncertainty in complex systems.
- This analysis contrasts frequentist and Bayesian methods.
"Bayesian statistics": The branch of statistics that applies probability to statistical problems, providing a mathematical procedure for updating beliefs in light of new evidence.
- Bayesian statistics offers a coherent framework for parameter estimation.
"Bayesian network": A probabilistic graphical model that represents a set of variables and their conditional dependencies via a directed acyclic graph.
- The system's reliability was modeled using a Bayesian network.
"Bayesian prior/posterior": Key components in Bayesian inference. The "prior" represents initial beliefs about a parameter before seeing data. The "posterior" represents the updated beliefs after considering the evidence.
- The choice of an informative prior significantly influenced the posterior distribution.
Bayesianism (noun): The philosophical interpretation or advocacy of the Bayesian approach to probability.
- His work is grounded in a firm belief in Bayesianism.
Bayes' theorem (noun): The fundamental mathematical rule at the core of Bayesian methods, describing how to update the probability for a hypothesis as more evidence becomes available.
- The calculation is a direct application of Bayes' theorem.
- Probabilistic (in a specific context): Involving or based on probability, though this is a broader term.
- Evidential: Relating to or based on evidence, which aligns with the Bayesian principle of updating beliefs.
"Empirical Bayes method": A statistical approach that uses observed data to estimate the prior distribution in a Bayesian analysis.
- The empirical Bayes method was used to borrow strength across similar experiments.
"Fully Bayesian analysis": An analysis that treats all unknown parameters as random variables and uses prior distributions for each.
- The paper presents a fully Bayesian analysis of the hierarchical model.
- of or relating to statistical methods based on Bayes' theorem