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A bimodal Weibull distribution: properties and inference.
Vila, Roberto; Niyazi Çankaya, Mehmet.
Afiliação
  • Vila R; Departamento de Estatística, Universidade de Brasília, Brasília, Brazil.
  • Niyazi Çankaya M; Faculty of Applied Sciences, Department of International Trading and Finance, Usak University, Usak, Turkey.
J Appl Stat ; 49(12): 3044-3062, 2022.
Article em En | MEDLINE | ID: mdl-36035615
Modelling is challenging topic and using parametric models is important stage to reach flexible function for modelling. Weibull distribution has shape and scale parameters which play the main role for modelling. Bimodality parameter is added and so bimodal Weibull distribution can capture real data set with bimodality which can be actually combination of two populations. The properties of the proposed distribution and estimation method are examined extensively to show its usability in modelling accurately and safely for practitioners. After examination as first stage in modelling issue, it is appropriate to use bimodal Weibull for modelling bimodality in real data sets if it exists. Two estimation methods including objective functions are used to estimate the parameters of shape, scale and bimodality parameters of function. The second stage in modelling is overcome by using heuristic algorithms for optimization of function according to parameters due to the fact that converging to global point of objective function is performed by heuristic algorithms from stochastic optimization. Real data sets are provided to show the modelling competence of objective functions from bimodal forms of Weibull and Gamma distributions having well defined shape, scale and bimodality parameters and potentially less parameters when compared with the existing distributions.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: J Appl Stat Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Brasil País de publicação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: J Appl Stat Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Brasil País de publicação: Reino Unido