Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/108966
Title: A finite mixture of multiple discrete distributions for modelling heaped count data
Author: Bermúdez, Lluís
Karlis, Dimitris
Santolino, Miguel
Keywords: Anàlisi de regressió
Assegurances d'accidents
Variables (Matemàtica)
Regression analysis
Accident insurance
Variables (Mathematics)
Issue Date: 24-Feb-2017
Publisher: Elsevier B.V.
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.
Note: Versió postprint del document publicat a: https://doi.org/10.1016/j.csda.2017.02.013
It is part of: Computational Statistics & Data Analysis, 2017, vol. 112, num. August, p. 14-23
Related resource: https://doi.org/10.1016/j.csda.2017.02.013
URI: http://hdl.handle.net/2445/108966
ISSN: 0167-9473
Appears in Collections:Articles publicats en revistes (Matemàtica Econòmica, Financera i Actuarial)

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