Data · collection · 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/collections/Semiparametric_Estimation_of_Gamma_Processes_for_D… ↗
landing page · from DataCite
- Repository landing page tandf.figshare.com/collections/Semiparametric_Estimation_of_Gamma_Processes_for_D… ↗
landing page · from DataCite
- DOI doi.org/10.6084/m9.figshare.c.2029151 ↗
DOI / persistent id · from DataCite
- DOI doi.org/10.6084/m9.figshare.c.2029151.v1 ↗
DOI / persistent id · from DataCite
Documentation and papers
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Topics
- Stated by source
- Biological sciences · Biological sciences · Mathematics · Mathematics
- From keywords
- Ecology · Genetics · Life Sciences · Life Sciences · Mathematics & Statistics · Mathematics & Statistics
- Inferred from text
- Simulation 75%
Related
- Possibly the same asSemiparametric Estimation of Gamma Processes for Deteriorating Products
Provenance · 2 source records, 16 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| DataCite | 10.6084/m9.figshare.c.2029151 | 13 d ago | JSON v1 |
| DataCite | 10.6084/m9.figshare.c.2029151.v1 | 13 d ago | JSON v1 |
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