Bayesian methods in statistics – article review -

this approach relies on the methodical integration of previous beliefs (expressed through initial distributions) with fresh data obtained from real-world experiments (using a probability function). In sophisticated computations, Bayesian statistics presents difficulties despite its many benefits. However, these difficulties have been largely overcome because to developments in simulation methods like the MCMC. The MH algorithm, Gs, MCH, and NUTS technique are the four main algorithms that are examined in this paper within the MCMC framework. The study compares the benefits of the Bayesian approach, such as model design flexibility and uncertainty management, with its drawbacks.