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Inverse Batschelet distributions for circular data.
Jones, M C; Pewsey, Arthur.
Afiliación
  • Jones MC; Department of Mathematics & Statistics, The Open University, Walton Hall, Milton Keynes, UK. m.c.jones@open.ac.uk
Biometrics ; 68(1): 183-93, 2012 Mar.
Article en En | MEDLINE | ID: mdl-22443354
ABSTRACT
We provide four-parameter families of distributions on the circle which are unimodal and display the widest ranges of both skewness and peakedness yet available. Our approach is to transform the scale of a generating distribution, such as the von Mises, using various nontrivial extensions of an approach first used in Batschelet's (1981, Circular Statistics in Biology) book. The key is to employ inverses of Batschelet-type transformations in certain ways; these exhibit considerable advantages over direct Batschelet transformations. The skewness transformation is especially appealing as it has no effect on the normalizing constant. As well as a variety of interesting theoretical properties, when likelihood inference is explored these distributions display orthogonality between elements of a pairing of parameters into (location, skewness) and (concentration, peakedness). Further, the location parameter can sometimes be made approximately orthogonal to all the other parameters. Profile likelihoods come to the fore in practice. Two illustrative applications, one concerning the locomotion of a Drosophila fly larva, the other analyzing a large set of sudden infant death syndrome data, are investigated.
Asunto(s)

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Distribuciones Estadísticas / Interpretación Estadística de Datos / Modelos Estadísticos / Biometría Tipo de estudio: Risk_factors_studies Idioma: En Revista: Biometrics Año: 2012 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Distribuciones Estadísticas / Interpretación Estadística de Datos / Modelos Estadísticos / Biometría Tipo de estudio: Risk_factors_studies Idioma: En Revista: Biometrics Año: 2012 Tipo del documento: Article País de afiliación: Reino Unido