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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 |
URI: | http://hdl.handle.net/2445/108966 |
Related resource: | https://doi.org/10.1016/j.csda.2017.02.013 |
ISSN: | 0167-9473 |
Appears in Collections: | Articles publicats en revistes (Matemàtica Econòmica, Financera i Actuarial) |
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670360.pdf | 364.23 kB | Adobe PDF | View/Open |
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