Data · dataset · 2015
Semiparametric Estimation of Gamma Processes for Deteriorating Products
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This article investigates the semiparametric inference of the simple Gamma-process model and a random-effects variant.
Description
Maximum likelihood estimates of the parameters are obtained through the EM algorithm. The bootstrap is used to construct confidence intervals.
A simulation study reveals that an estimation based on the full likelihood method is more efficient than the pseudo likelihood method. In addition, a score test is developed to examine the existence of random effects under the semiparametric scenario. A comparison study using a fatigue-crack growth dataset shows that performance of a semiparametric estimation is comparable to the parametric counterpart.
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- Repository landing page tandf.figshare.com/articles/dataset/Semiparametric_Estimation_of_Gamma_Processes_… ↗
landing page · from DataCite
- DOI doi.org/10.6084/m9.figshare.1266501 ↗
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Documentation and papers
- Creative Commons Attribution 4.0 International creativecommons.org/licenses/by/4.0/legalcode ↗
license · from DataCite
- IsSupplementTo 10.1080/00401706.2013.869261 doi.org/10.1080/00401706.2013.869261 ↗
publication · from DataCite
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- DataCite API api.datacite.org/dois/10.6084/m9.figshare.1266501 ↗
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Topics
- Stated by source
- Biological sciences · Mathematics
- From keywords
- Ecology · Genetics · Life Sciences · Mathematics & Statistics
- Inferred from text
- Simulation 75%
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- Possibly the same asSemiparametric Estimation of Gamma Processes for Deteriorating Products
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