Abstract
In this paper, we propose two new simple estimation methods for the two-parameter gamma distribution. The first one is a modified version of the method of moments, whereas the second one makes use of some key properties of the distribution. We then derive the asymptotic distributions of these estimators. Also, bias-reduction methods are suggested to reduce the bias of these estimators. The performance of the estimators are evaluated through a Monte Carlo simulation study. The probability coverages of confidence intervals are also discussed. Finally, two examples are used to illustrate the proposed methods.
| Original language | English |
|---|---|
| Pages (from-to) | 2425-2437 |
| Number of pages | 13 |
| Journal | Communications in Statistics: Simulation and Computation |
| Volume | 48 |
| Issue number | 8 |
| DOIs | |
| Publication status | Published - 14 Sept 2019 |
Keywords
- Gamma distribution
- Maximum likelihood estimator
- Method of moments
- Modified moment estimator
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