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Change of Variables theorem to fit Bimodal Distributions

  • Camilla Ferretti
  • , Zammori Francesco

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Bimodality is observed in empirical distributions of variables related\r\nto materials (glass resistance), companies (productivity) and natural phenomena\r\n(geyser eruption). Our proposal for modeling bimodality exploits the change of\r\nvariables theorem requiring the choice of a generating density function which represents\r\nthe main features of the phenomena under analysis, and the choice of the\r\ntransforming function ϕ(x) that describes the observed departure from the expected\r\nbehaviour. The novelty of this work consists in putting attention to the choice of\r\nϕ(x) in two different cases: when bimodality arises from a slight departure from\r\nunimodality and when it is a proper structural feature of the variable under study.\r\nAs an example we use the R ”geyser” dataset.
Original languageEnglish
Title of host publicationSIS 2017 Statistics and Data Science: new challenges, new generations
PublisherFirenze University Press
Pages417-422
Number of pages6
ISBN (Print)978-88-6453-521-0
Publication statusPublished - 2017

Keywords

  • bimodal density function
  • change of variables theorem

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