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Parametric Bootstrap Methods for Estimating Model Parameters of Non-homogeneous Gamma Process
| Content Provider | Semantic Scholar |
|---|---|
| Author | Saito, Yasuhiro Dohi, Tadashi |
| Copyright Year | 2017 |
| Abstract | Non-Homogeneous Gamma Process (NHGP) is characterized by an arbitrary trend function and a gamma renewal distribution. In this paper, we estimate the confidence intervals of model parameters of NHGP via two parametric bootstrap methods: simulation-based approach and re-sampling-based approach. For each bootstrap method, we apply three methods to construct the confidence intervals. Through simulation experiments, we investigate each parametric bootstrapping and each construction method of confidence intervals in terms of the estimation accuracy. Finally, we find the best combination to estimate the model parameters in trend function and gamma renewal distribution in NHGP. KeywordsBootstrap, Non-homogeneous gamma process, Trend function, Confidence interval. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.ijmems.in/assets/13-vol.-3,-no.-2,-167%E2%80%93176,-2018.pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Bootstrapping (compilers) Bootstrapping (statistics) Confidence Intervals Estimated Experiment QT interval feature (observable entity) Resampling (statistics) Sampling (signal processing) Simulation |
| Content Type | Text |
| Resource Type | Article |
