dc.contributor.author
Bermúdez, Lluís
dc.contributor.author
Karlis, Dimitris
dc.contributor.author
Santolino, Miguel
dc.date.issued
2017-03-27T12:39:52Z
dc.date.issued
2019-02-24T06:10:14Z
dc.date.issued
2017-02-24
dc.date.issued
2017-03-27T12:39:53Z
dc.identifier
https://hdl.handle.net/2445/108966
dc.description.abstract
A new modelling approach, based on finite mixtures of multiple discrete distributions of different multiplicities, is proposed to fit data with a lot of periodic spikes in certain values. An EM algorithm is provided in order to ensure the models' ease-of-fit and then a simulation study is presented to show its efficiency. A numerical application with a real data set involving the length, measured in days, of inability to work after an accident occurs is treated. The main finding is that the model provides a very good fit when working week, calendar week and month multiplicities are taken into account.
dc.format
application/pdf
dc.publisher
Elsevier B.V.
dc.relation
Versió postprint del document publicat a: https://doi.org/10.1016/j.csda.2017.02.013
dc.relation
Computational Statistics & Data Analysis, 2017, vol. 112, num. August, p. 14-23
dc.relation
https://doi.org/10.1016/j.csda.2017.02.013
dc.rights
cc-by-nc-nd (c) Elsevier B.V., 2017
dc.rights
http://creativecommons.org/licenses/by-nc-nd/3.0/es
dc.rights
info:eu-repo/semantics/openAccess
dc.source
Articles publicats en revistes (Matemàtica Econòmica, Financera i Actuarial)
dc.subject
Anàlisi de regressió
dc.subject
Assegurances d'accidents
dc.subject
Variables (Matemàtica)
dc.subject
Regression analysis
dc.subject
Accident insurance
dc.subject
Variables (Mathematics)
dc.title
A finite mixture of multiple discrete distributions for modelling heaped count data
dc.type
info:eu-repo/semantics/article
dc.type
info:eu-repo/semantics/acceptedVersion