No abstract

The proposed article is devoted to the application of the Bayesian approach to the construction of statistical estimates of the parameters of the laws of distribution of random variables. Four distribution laws are considered: the Poisson law, the exponential law, the uniform law, and the Pareto law are presented. The results of constructing point estimates and interval estimates for the parameters of these laws. The results of comparison with the corresponding statistical estimates constructed by the classical maximum likelihood method are presented too. The proposed algorithm can be effectively applied in the development of measurement methods, in solving measurement problems, in the development of practical methods for identifying systematic measurement errors.