Closeness of Lindley distribution to Weibull and gamma distributions
| Autor: | D. K. Al-Mutairi, Mohammad Z. Raqab, R. A. Al-Jarallah |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Statistics and Probability
Weibull modulus Applied Mathematics Model selection Generalized gamma distribution 02 engineering and technology 01 natural sciences 010104 statistics & probability Skewness Modeling and Simulation Likelihood-ratio test Statistics 0202 electrical engineering electronic engineering information engineering Gamma distribution Statistics::Methodology 020201 artificial intelligence & image processing 0101 mathematics Statistics Probability and Uncertainty Exponentiated Weibull distribution Finance Weibull distribution Mathematics |
| Zdroj: | Communications for Statistical Applications and Methods. 24:129-142 |
| ISSN: | 2383-4757 |
| DOI: | 10.5351/csam.2017.24.2.129 |
| Popis: | In this paper we consider the problem of the model selection/discrimination among three different positively skewed lifetime distributions. Lindley, Weibull, and gamma distributions have been used to effectively analyze positively skewed lifetime data. This paper assesses how much closer the Lindley distribution gets to Weibull and gamma distributions. We consider three techniques that involve the likelihood ratio test, asymptotic likelihood ratio test, and minimum Kolmogorov distance as optimality criteria to diagnose the appropriate fitting model among the three distributions for a given data set. Monte Carlo simulation study is performed for computing the probability of correct selection based on the considered optimality criteria among these families of distributions for various choices of sample sizes and shape parameters. It is observed that overall, the Lindley distribution is closer to Weibull distribution in the sense of likelihood ratio and Kolmogorov criteria. A real data set is presented and analyzed for illustrative purposes. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|