ArticleJournal of applied statistics2022
A bimodal Weibull distribution: properties and inference.
Article in Journal of applied statistics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Moss Cover Redirects Soil Organic Carbon from Active Turnover to Mineral-Associated Stabilization in Subalpine Forests.Plants (Basel, Switzerland) · 2026Article
- A model for bimodal rates and proportions.Journal of applied statistics · 2024Article
- A general class of trimodal distributions: properties and inference.Journal of applied statistics · 2024Article
- Article
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2 authors.
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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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