Bimodality based on the generalized skew-normal distribution

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dc.contributor.authorVenegas, Osvaldo
dc.contributor.authorSalinas, Hugo S.
dc.contributor.authorGallardo, Diego I.
dc.contributor.authorBolfarine, Heleno
dc.contributor.authorGómez, Héctor W.
dc.date2018
dc.date.accessioned2020-01-07T20:04:17Z
dc.date.available2020-01-07T20:04:17Z
dc.description.abstractThis paper focuses on the development of a new extension of the generalized skew-normal distribution introduced in Gomez et al. [Generalized skew-normal models: properties and inference. Statistics. 2006;40(6):495-505]. To produce the generalization a new parameter is introduced, the signal of which has the flexibility of yielding unimodal as well as bimodal distributions. We study its properties, derive a stochastic representation and state some expressions that facilitate moments derivation. Maximum likelihood is implemented via the EM algorithm which is based on the stochastic representation derived. We show that the Fisher information matrix is singular and discuss ways of getting round this problem. An illustration using real data reveals that the model can capture well special data features such as bimodality and asymmetryen_US
dc.formatPDFen_US
dc.identifier.citationJournal of Statistical Computation and Simulation, Vol.88, N° 1, 156-181, 2018en_US
dc.identifier.doi10.1080/00949655.2017.1381698en_US
dc.identifier.urihttp://repositoriodigital.uct.cl/handle/10925/2137
dc.language.isoenen_US
dc.sourceJournal of Statistical Computation and Simulationen_US
dc.subjectAsimetríaen_US
dc.subjectCurtosisen_US
dc.subjectEstimación de máxima verosimilituden_US
dc.subjectDistribución sesgada normalen_US
dc.titleBimodality based on the generalized skew-normal distributionen_US
dc.typeArtículo de Revistaen_US
uct.catalogadorpopen_US
uct.comunidadIngenieríaen_US
uct.facultadFacultad de Ingenieríaen_US
uct.indizacionISI - Science Citation Indexen_US
uct.indizacionSCOPUSen_US
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