Open AccessThe integrals and integral transformations connected with the joint vector Gaussian distribution
Author(s) -
В. С. Муха,
Н. Ф. Како
Publication year - 2021
Publication title -
vescì nacyânalʹnaj akadèmìì navuk belarusì. seryâ fìzìka-matèmatyčnyh navuk
Language(s) - English
Resource type - Journals
eISSN - 2524-2415
pISSN - 1561-2430
DOI - 10.29235/1561-2430-2021-57-2-206-216
Subject(s) - mathematics , joint probability distribution , probability density function , gaussian integral , gaussian , multivariate random variable , probability distribution , multiple integral , gaussian function , random variable , mathematical analysis , statistics , physics , quantum mechanics
In many applications it is desirable to consider not one random vector but a number of random vectors with the joint distribution. This paper is devoted to the integral and integral transformations connected with the joint vector Gaussian probability density function. Such integral and transformations arise in the statistical decision theory, particularly, in the dual control theory based on the statistical decision theory. One of the results represented in the paper is the integral of the joint Gaussian probability density function. The other results are the total probability formula and Bayes formula formulated in terms of the joint vector Gaussian probability density function. As an example the Bayesian estimations of the coefficients of the multiple regression function are obtained. The proposed integrals can be used as table integrals in various fields of research.