Bayesian statistics (/ˈbeɪziən/ BAY-zee-ən or /ˈbeɪʒən/ BAY-zhən) is a theory in the field of statistics based on the Bayesian interpretation of probability...

Bayesian inference is an important technique in statistics, and especially in mathematical statistics. Bayesian updating is particularly important in the dynamic...

Bayesian probability (/ˈbeɪziən/ BAY-zee-ən or /ˈbeɪʒən/ BAY-zhən) is an interpretation of the concept of probability, in which, instead of frequency or...

such as Bayesian inference, each of which can be considered to have their own sequence in the development of the ideas underlying modern statistics. By the...

account for the availability of related evidence. Bayesian inference is fundamental to Bayesian statistics. It has been considered to be "to the theory of...

several distinct meanings in different branches of statistics. In statistics, especially in Bayesian statistics, the kernel of a probability density function...

In statistics, the Bayesian information criterion (BIC) or Schwarz information criterion (also SIC, SBC, SBIC) is a criterion for model selection among...

In game theory, a Bayesian game is a strategic decision-making model which assumes players have incomplete information. Players hold private information...

A Bayesian network (also known as a Bayes network, Bayes net, belief network, or decision network) is a probabilistic graphical model that represents a...

has a variety of interpretations including in terms of geometry, Bayesian statistics and convex analysis. The LASSO is closely related to basis pursuit...