Literature DB >> 36035615

A bimodal Weibull distribution: properties and inference.

Roberto Vila1, Mehmet Niyazi Çankaya2,3.   

Abstract

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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Entities:  

Keywords:  Bimodal distribution; Weibull distribution; estimation; modelling; q-inference

Year:  2021        PMID: 36035615      PMCID: PMC9415601          DOI: 10.1080/02664763.2021.1931822

Source DB:  PubMed          Journal:  J Appl Stat        ISSN: 0266-4763            Impact factor:   1.416


  6 in total

1.  The beta modified Weibull distribution.

Authors:  Giovana O Silva; Edwin M M Ortega; Gauss M Cordeiro
Journal:  Lifetime Data Anal       Date:  2010-03-18       Impact factor: 1.588

2.  Mixture and non-mixture cure fraction models based on the generalized modified Weibull distribution with an application to gastric cancer data.

Authors:  Edson Z Martinez; Jorge A Achcar; Alexandre A A Jácome; José S Santos
Journal:  Comput Methods Programs Biomed       Date:  2013-08-06       Impact factor: 5.428

3.  Information Geometric Duality of ϕ-Deformed Exponential Families.

Authors:  Jan Korbel; Rudolf Hanel; Stefan Thurner
Journal:  Entropy (Basel)       Date:  2019-01-24       Impact factor: 2.524

4.  Asymmetric Bimodal Exponential Power Distribution on the Real Line.

Authors:  Mehmet Niyazi Çankaya
Journal:  Entropy (Basel)       Date:  2018-01-03       Impact factor: 2.524

5.  The bimodality index: a criterion for discovering and ranking bimodal signatures from cancer gene expression profiling data.

Authors:  Jing Wang; Sijin Wen; W Fraser Symmans; Lajos Pusztai; Kevin R Coombes
Journal:  Cancer Inform       Date:  2009-08-05

Review 6.  The expression level of angiotensin-converting enzyme 2 determines the severity of COVID-19: lung and heart tissue as targets.

Authors:  Mohammad Mahdi Nejadi Babadaei; Anwarul Hasan; Samir Haj Bloukh; Zehra Edis; Majid Sharifi; Ehsan Kachooei; Mojtaba Falahati
Journal:  J Biomol Struct Dyn       Date:  2020-06-01
  6 in total

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