UDC 519.226.3
DOI: 10.36871/2618-9976.2022.04.003
Authors
Zvyagin L.S.
PhD of Economics, Associate Professor, Financial University under the Government of the Russian
Federation, Associate Professor of the Department "System analysis in economics", Moscow, Russia
Abstract
Interpretation of the real parameters of the model is the main distinguishing feature of the Bayesian approach from the classical methods, which claim that it is not the parameters that are random, but their estimates, which are observation functions that include elements of randomness. In contrast, Bayesian methods claim that the randomness of parameters is a property of the real world, as well as the fact that every physical object is subject to constant random variations. Based on the Bayesian approach, the estimates of these parameters are not random, so they should be calculated. An example of such estimates is the average value of a random variable. Bayes' theorem is widely used to solve many statistical problems, and the Bayesian approach is necessary in order to draw correct conclusions about the parameters of the econometric model obtained on the basis of sample data.
Keywords
Bayesian approach, Modeling, Analysis, Processes and algorithms, A priori distributions, General population
