title: ÐÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ðµ Ð¾ÑÐµÐ½Ð¾Ðº Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÐ¾Ð² Ð¿Ð¾Ð»Ð¾Ð¶ÐµÐ½Ð¸Ñ, Ð¼Ð°ÑÑÑÐ°Ð±Ð° Ð¸ ÐºÐ¾ÑÑÐµÐ»ÑÑÐ¸Ð¸ ÐºÐ»Ð°ÑÑÐ° Ð´Ð²ÑÐ¼ÐµÑÐ½ÑÑ ÑÐ°ÑÐ¿ÑÐµÐ´ÐµÐ»ÐµÐ½Ð¸Ð¹ Ñ Ð½ÐµÐ·Ð°Ð²Ð¸ÑÐ¸Ð¼ÑÐ¼Ð¸ ÐºÐ¾Ð¼Ð¿Ð¾Ð½ÐµÐ½ÑÐ°Ð¼Ð¸
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÐ°
titleType: Subtitle
title: Study of the location, scale and correlation parameters of the class of bivariate independent component distribution
Creators: name: ÐÑÐ°ÑÐºÐµÐ²Ð¸Ñ, Ð¡ÐµÑÐ³ÐµÐ¹
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2020
Subjects: Ð´Ð²ÑÐ¼ÐµÑÐ½Ð¾Ðµ ÑÐ°ÑÐ¿ÑÐµÐ´ÐµÐ»ÐµÐ½Ð¸Ðµ Ñ Ð½ÐµÐ·Ð°Ð²Ð¸ÑÐ¸Ð¼ÑÐ¼Ð¸ ÐºÐ¾Ð¼Ð¿Ð¾Ð½ÐµÐ½ÑÐ°Ð¼Ð¸
Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÐ¸ÑÐµÑÐºÐ¸Ðµ Ð¾ÑÐµÐ½ÐºÐ¸
Ð¼ÐµÑÐ¾Ð´ Ð¼Ð°ÐºÑÐ¸Ð¼Ð°Ð»ÑÐ½Ð¾Ð³Ð¾ Ð¿ÑÐ°Ð²Ð´Ð¾Ð¿Ð¾Ð´Ð¾Ð±Ð¸Ñ
Ð¿Ð°ÑÐ°Ð¼ÐµÑÑ Ð¿Ð¾Ð»Ð¾Ð¶ÐµÐ½Ð¸Ñ
Ð¿Ð°ÑÐ°Ð¼ÐµÑÑ Ð¼Ð°ÑÑÑÐ°Ð±Ð°
Ð¿Ð°ÑÐ°Ð¼ÐµÑÑ ÐºÐ¾ÑÑÐµÐ»ÑÑÐ¸Ð¸
Ð°ÑÐ¸Ð¼Ð¿ÑÐ¾ÑÐ¸ÑÐµÑÐºÐ°Ñ Ð´Ð¸ÑÐ¿ÐµÑÑÐ¸Ñ
Ð¸Ð½ÑÐ¾ÑÐ¼Ð°ÑÐ¸Ñ Ð¤Ð¸ÑÐµÑÐ°
independent component distribution
parametric estimates
maximum likelihood estimation method
location parameter
scale parameter
correlation parameter
asymptotic variance
Fisher information

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description: The given work is devoted to the construction and analysis of maximum likelihood estimates (MLEs) for the class of bivariate independent component distribution (ICD). In the course of work, the following tasks were solved: 1. Search for analytical expressions of maximum likelihood estimates of the class of bivariate ICD. The estimates were searched for the three cases when for the one-dimensional distribution defining the particular form of ICD is used the normal, Laplace and Cauchy distributions. 2. Development and implementation of a software package for calculating the constructed estimates. 3. Obtaining statistical properties of estimates, for example, Fisher information. 4. Verification of the results using the Monte Carlo method. As a result, MLEs were obtained for all three parameters (position, scale, and correlation) for each case of one-dimensional distribution. Algorithms for calculating these estimates were developed and implemented. In those cases where it was not possible to obtain an explicit form of the estimate, numerical procedures for their calculation were proposed and implemented. The obtained theoretical calculations were confirmed experimentally. Thus, it can be said that in the given work the MLEs for the class of bivariate ICD are developed. The obtained results make it possible to rationalize the choice of an algorithm for processing data distributed according to bivariate ICD.