Discriminating between the log-normal and generalized exponential distributions
- 作者：Kundu ; Debasis ; D. Gupta ; Rameshwar ; Manglick ; Anubhav
- 关键词：Asymptotic distributions ; Generalized exponential distribution ; Kolmogorov&ndash ; Smirnov distances ; Likelihood ratio test statistic
- 刊名：Journal of Statistical Planning and Inference
- 出版年：2005
- 期刊代码：36_03783758
- 类别：mt
- 出版时间：January 1, 2005
- 卷：127
- 期：1-2
- 页码：213-227
- 文件大小：250 K
摘要
The two-parameter generalized exponential distribution was recently introduced by Gupta and Kundu (Austral. New Zealand J. Statist. 40 (1999) 173). It is observed that the Generalized Exponential distribution can be used quite effectively to analyze skewed data set as an alternative to the more popular log-normal distribution. In this paper, we use the ratio of the maximized likelihoods in choosing between the log-normal and generalized exponential distributions. We obtain asymptotic distributions of the logarithm of the ratio of the maximized likelihoods and use them to determine the required sample size to discriminate between the two distributions for a user specified probability of correct selection and tolerance limit.