Please use this identifier to cite or link to this item: http://hdl.handle.net/10174/19205

Title: Application of Mixture Models to Survival Data
Authors: Madeira, Sílvia
Infante, Paulo
Didelet, Filipe
Editors: Sinha, Jyoti K.
Keywords: Reliability
Mixture-models
Censored data
Survival models
Inspection Policies
Issue Date: 2016
Publisher: ShieldCrest Publishing Limited
Citation: Madeira, S.; Infante; P.; Didelet;F. (2016). Application of Mixture Models to Survival Data. In Journal of Maintenance Engineering. (1 ed., Vol. 1, pp. 366-374). Aylesbury, Buckinghamshire: ShieldCrest Publishing.
Abstract: Survival models are being widely applied to the engineering field to model time-to-event data once censored data is here a common issue. Using parametric models or not, for the case of heterogeneous data, they may not always represent a good fit. The present study relays on critical pumps survival data where traditional parametric regression might be improved in order to obtain better approaches. Considering censored data and using an empiric method to split the data into two subgroups to give the possibility to fit separated models to our censored data, we’ve mixture two distinct distributions according a mixture-models approach. We have concluded that it is a good method to fit data that does not fit to a usual parametric distribution and achieve reliable parameters. A constant cumulative hazard rate policy was used as well to check optimum inspection times using the obtained model from the mixture-model, which could be a plus when comparing with the actual maintenance policies to check whether changes should be introduced or not.
URI: http://hdl.handle.net/10174/19205
ISBN: 978-1-911090-39-7
Type: bookPart
Appears in Collections:CIMA - Publicações - Capítulos de Livros
MAT - Publicações - Capítulos de Livros

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