Change of Variables theorem to fit Bimodal Distributions

Camilla Ferretti, Piero Ganugi, Zammori Francesco

Risultato della ricerca: Contributo in libroContributo a convegno

Abstract

Bimodality is observed in empirical distributions of variables related to materials (glass resistance), companies (productivity) and natural phenomena (geyser eruption). Our proposal for modeling bimodality exploits the change of variables theorem requiring the choice of a generating density function which represents the main features of the phenomena under analysis, and the choice of the transforming function ϕ(x) that describes the observed departure from the expected behaviour. The novelty of this work consists in putting attention to the choice of ϕ(x) in two different cases: when bimodality arises from a slight departure from unimodality and when it is a proper structural feature of the variable under study. As an example we use the R ”geyser” dataset.
Lingua originaleEnglish
Titolo della pubblicazione ospiteSIS 2017 Statistics and Data Science: new challenges, new generations
Pagine417-422
Numero di pagine6
Stato di pubblicazionePubblicato - 2017
EventoSIS 2017 Statistical Conference - Florence
Durata: 28 giu 201730 giu 2017

Convegno

ConvegnoSIS 2017 Statistical Conference
CittàFlorence
Periodo28/6/1730/6/17

Keywords

  • bimodal density function
  • change of variables theorem

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