General EM Algorithm for Fitting Non-Monotone Hazard Functions from Truncated and Censored Observations
SCIE
SCOPUS
- Title
- General EM Algorithm for Fitting Non-Monotone Hazard Functions from Truncated and Censored Observations
- Authors
- BARDE, STEPHANE; KO, YOUNG MYOUNG; SHIN, HAYONG
- Date Issued
- 2022-09
- Publisher
- Elsevier BV
- Abstract
- Recently, many researchers focused on modeling non-monotonic hazard functions such as bath-tube and hump shapes. However, most of their estimation methods are focused on complete observations. Since reliability data are typically censored and truncated, a general EM algorithm is proposed, which can fit any of those complex hazard functions. The proposed EM algorithm is analyzed by fitting well-known 4-parameter hazard functions, where its performance is compared by their specific direct methods through extensive Monte Carlo simulations. (c) 2022 Elsevier B.V. All rights reserved.
- URI
- https://oasis.postech.ac.kr/handle/2014.oak/113383
- DOI
- 10.1016/j.orl.2022.07.001
- ISSN
- 0167-6377
- Article Type
- Article
- Citation
- Operations Research Letters, vol. 50, no. 5, page. 476 - 483, 2022-09
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- There are no files associated with this item.
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