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Jackknife empirical likelihood test for testing one-sided Lévy distribution.
Deepesh Bhati1, Sudheesh K Kattumannil2
1Department of Statistics, Central University of Rajasthan, Ajmer, India.
Journal of Applied Statistics
|June 16, 2022
Summary
This study introduces a new statistical test for one-sided Lévy distributions using a jackknife empirical likelihood method. The developed tests demonstrate strong power in simulations and are applied to real-world data.
Area of Science:
- Statistics
- Probability Theory
Background:
- Lévy distributions are important in probability and statistics.
- Existing methods for testing one-sided Lévy distributions may have limitations.
Purpose of the Study:
- To develop a novel jackknife empirical likelihood-based test for one-sided Lévy distributions.
- To create an adjusted version of the test for improved performance.
Main Methods:
- Construction of a U-empirical process.
- Application of jackknife empirical likelihood techniques.
- Development of an adjusted jackknife empirical likelihood test.
Main Results:
- The proposed tests exhibit very good statistical power against various alternatives.
- Simulation studies confirm the effectiveness of the new tests.
Conclusions:
- The jackknife empirical likelihood-based tests are effective for detecting one-sided Lévy distributions.
- The methodology is illustrated with practical applications on real datasets.
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