Estimation of Concentrations Parameters in the Model of Mixture with Varying Concentrations

Model of Mixture with Varying Concentrations (MVC) is a generalization of the finite mixture model (FMM) at which the mixing probabilities (concentrations of components in the mixture) vary from observation to observation. In this paper we assume that the components' distributions are complete...

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Main Authors: Rostyslav Maiboroda, Vitaliy Miroshnychenko, Olena Sugakova
Format: Article
Language:English
Published: Austrian Statistical Society 2025-01-01
Series:Austrian Journal of Statistics
Online Access:https://www.ajs.or.at/index.php/ajs/article/view/1953
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author Rostyslav Maiboroda
Vitaliy Miroshnychenko
Olena Sugakova
author_facet Rostyslav Maiboroda
Vitaliy Miroshnychenko
Olena Sugakova
author_sort Rostyslav Maiboroda
collection DOAJ
description Model of Mixture with Varying Concentrations (MVC) is a generalization of the finite mixture model (FMM) at which the mixing probabilities (concentrations of components in the mixture) vary from observation to observation. In this paper we assume that the components' distributions are completely unknown, while the concentrations are known up to some unknown euclidean parameter. Two approaches are considered to the semiparametric estimation of this parameter in the case of two-component mixture. The Least Squares (LS) estimator is based on fitting the distribution functions of the observations. The Empirical Maximum Likelihood estimator (EML) utilizes some empirical version of the likelihood function. Consistency of the LS estimator is demonstrated. A fast algorithm for the LS estimator calculation is presented. EML and LS estimators are compared via simulations. Both EML and LS estimators show sufficiently good performance in all the experiments. The LS estimator performed better then the EML one for components with different variance. The EML estimator outperformed the LS one for nongaussian components with asymmetric tails.
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institution Kabale University
issn 1026-597X
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publishDate 2025-01-01
publisher Austrian Statistical Society
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series Austrian Journal of Statistics
spelling doaj-art-28faa89b572c419ab31596f60233f8912025-01-13T07:12:23ZengAustrian Statistical SocietyAustrian Journal of Statistics1026-597X2025-01-0154110.17713/ajs.v54i1.1953Estimation of Concentrations Parameters in the Model of Mixture with Varying ConcentrationsRostyslav Maiboroda0Vitaliy MiroshnychenkoOlena SugakovaTaras Sevchenko National University of Kyiv Model of Mixture with Varying Concentrations (MVC) is a generalization of the finite mixture model (FMM) at which the mixing probabilities (concentrations of components in the mixture) vary from observation to observation. In this paper we assume that the components' distributions are completely unknown, while the concentrations are known up to some unknown euclidean parameter. Two approaches are considered to the semiparametric estimation of this parameter in the case of two-component mixture. The Least Squares (LS) estimator is based on fitting the distribution functions of the observations. The Empirical Maximum Likelihood estimator (EML) utilizes some empirical version of the likelihood function. Consistency of the LS estimator is demonstrated. A fast algorithm for the LS estimator calculation is presented. EML and LS estimators are compared via simulations. Both EML and LS estimators show sufficiently good performance in all the experiments. The LS estimator performed better then the EML one for components with different variance. The EML estimator outperformed the LS one for nongaussian components with asymmetric tails. https://www.ajs.or.at/index.php/ajs/article/view/1953
spellingShingle Rostyslav Maiboroda
Vitaliy Miroshnychenko
Olena Sugakova
Estimation of Concentrations Parameters in the Model of Mixture with Varying Concentrations
Austrian Journal of Statistics
title Estimation of Concentrations Parameters in the Model of Mixture with Varying Concentrations
title_full Estimation of Concentrations Parameters in the Model of Mixture with Varying Concentrations
title_fullStr Estimation of Concentrations Parameters in the Model of Mixture with Varying Concentrations
title_full_unstemmed Estimation of Concentrations Parameters in the Model of Mixture with Varying Concentrations
title_short Estimation of Concentrations Parameters in the Model of Mixture with Varying Concentrations
title_sort estimation of concentrations parameters in the model of mixture with varying concentrations
url https://www.ajs.or.at/index.php/ajs/article/view/1953
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AT vitaliymiroshnychenko estimationofconcentrationsparametersinthemodelofmixturewithvaryingconcentrations
AT olenasugakova estimationofconcentrationsparametersinthemodelofmixturewithvaryingconcentrations