2026-04-13T04:06:10Zhttps://recercat.cat/oai/request

oai:recercat.cat:2445/1089662025-12-05T05:56:14Zcom_2072_1057col_2072_478917col_2072_478919

A finite mixture of multiple discrete distributions for modelling heaped count data Bermúdez, Lluís Karlis, Dimitris Santolino, Miguel Anàlisi de regressió Assegurances d'accidents Variables (Matemàtica) Regression analysis Accident insurance Variables (Mathematics) 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. 2017-03-27T12:39:52Z 2019-02-24T06:10:14Z 2017-02-24 2017-03-27T12:39:53Z info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion Versió postprint del document publicat a: https://doi.org/10.1016/j.csda.2017.02.013 Computational Statistics & Data Analysis, 2017, vol. 112, num. August, p. 14-23 https://doi.org/10.1016/j.csda.2017.02.013 cc-by-nc-nd (c) Elsevier B.V., 2017 http://creativecommons.org/licenses/by-nc-nd/3.0/es info:eu-repo/semantics/openAccess Elsevier B.V. Articles publicats en revistes (Matemàtica Econòmica, Financera i Actuarial)