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• Published Subscription 13 Feb 2019

  Model Based Clustering using Finite Mixture Models of Lognormal Distribution

  By Deepana R., Kiruthika .

  Abstract: AbstractModel-based clustering consists of fitting a mixture model to data and identifying cluster with its components. This study discusses model-based clustering using a finite mixture of a univariate lognormal distribution with k components. In this study, lognormal mixture models for skewed data and also the estimation of mixing proportion by distance-based clustering have been considered. Parameter estimation is carried out by expectation maximization (EM) algorithm using different initialization approach using …

  Published in Research & Reviews : Journal of Statistics · Vol. 7, Issue 3, 2018 · pp. 58–67 Read article →