A Dual Frailty Model for Lifetime Analysis in Maritime Transportation

Henderson, Robin, Mihaylova, Ralitsa and Oman, Paul (2019) A Dual Frailty Model for Lifetime Analysis in Maritime Transportation. Lifetime Data Analysis, 25 (4). pp. 739-756. ISSN 1380-7870

[img]
Preview
Text (Final published version)
Henderson2019_Article_ADualFrailtyModelForLifetimeAn.pdf - Published Version
Available under License Creative Commons Attribution 4.0.

Download (1MB) | Preview
[img]
Preview
Text (Advance online version)
Henderson2019_Article_ADualFrailtyModelForLifetimeAn.pdf - Published Version
Available under License Creative Commons Attribution 4.0.

Download (1MB) | Preview
[img]
Preview
Text
DualFrailR1.pdf - Accepted Version

Download (644kB) | Preview
Official URL: https://doi.org/10.1007/s10985-019-09463-3

Abstract

We consider changes in ownership of commercial shipping vessels from an event history perspective. Each change in ownership can be influenced by the properties of the vessel itself, its age and history to date, the characteristics of both the seller and the buyer, and time-varying market conditions. Similar factors can aect the process of deciding when to scrap the vessel as no longer being economically viable. We consider a multi-state approach in which states are dened by the owning companies, a sale marks a transition, and scrapping of the vessel corresponds to moving to an absorbing state. We propose a dual frailty model that attempts to capture unexplained heterogeneity in the data, with one frailty term for the seller and one for the buyer. We describe a Monte Carlo Markov chain estimation procedure and verify its accuracy through simulations. We investigate the consequences of mistakenly ignoring frailty in these circumstances. We compare results from the frailty analysis with an analysis using xed eects only.

Item Type: Article
Uncontrolled Keywords: Bayes, Clarksea index, Ownership duration, Partial likelihood, Proportional intensity, Random efects, Sentiment
Subjects: G300 Statistics
Department: Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User: Becky Skoyles
Date Deposited: 07 Aug 2018 07:20
Last Modified: 01 Aug 2021 10:17
URI: http://nrl.northumbria.ac.uk/id/eprint/35198

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics