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Finite mixture modeling via REBMIX
ID Nagode, Marko (Author)

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Abstract
The REBMIX algorithm for fitting finite mixture models implemented in R package rebmix is presented. It provides functions for random univariate and multivariate finite mixture generation, the number of components, component weights and component parameter estimation, bootstrapping and the plotting of finite mixtures. It requires preprocessing of observations, information criterion and conditionally independent normal, lognormal, Weibull, gamma, binomial, Poisson or Dirac component densities. The algorithm optimizes the component parameters, mixing weights and number of components successively based on boundary conditions, such as the maximum number of components and number of bins or nearest neighbours. The algorithm is robust, time efficient and can be used either to assess an initial set of unknown parameters and number of components, e.g., for the EM algorithm, or as a standalone algorithm providing a good compromise between parametric and nonparametric methods of finite mixture estimation. Univariate and multivariate datasets are analysed for validation purposes.

Language:English
Keywords:continuous variables, discrete variables, mixture estimation, R packages
Work type:Article
Typology:1.01 - Original Scientific Article
Organization:FS - Faculty of Mechanical Engineering
Publication status:Published
Publication version:Version of Record
Year:2015
Number of pages:Str. 14-28
Numbering:Vol. 3, no. 2
PID:20.500.12556/RUL-115102 This link opens in a new window
UDC:517.51(045)
ISSN on article:2312-7767
DOI:10.5963/JAO0302001 This link opens in a new window
COBISS.SI-ID:13980699 This link opens in a new window
Publication date in RUL:14.04.2020
Views:1566
Downloads:1118
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Secondary language

Language:Slovenian
Keywords:zvezne spremenljivke, diskretne spremenljivke, ocenjevanje mešanih porazdelitev, R paketi

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