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A finite mixture of multiple discrete distributions for modelling heaped count data

Author:
Bermúdez, Lluís, Karlis, Dimitris, Santolino, Miguel
Source:
Computational statistics & data analysis 2017 v.112 pp. 14-23
ISSN:
0167-9473
Subject:
accidents, algorithms, data collection, models
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.
Agid:
6100309