Developed One-parameter Lindley Distribution Using the Log-expo Transformation
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Abstract
The purposes of this study are to develop a one-parameter Lindley distribution using the log-expo transformation (LET-Lindley) and truncating the developed Lindley distribution (TLET-Lindley). The proposed distributions are presented in term of the survival function, hazard function, moment and parameter estimation using maximum likelihood. Moreover, the new distributions are applied in three real lifetime datasets. The results show that the proposed distributions are a better fit for the real datasets than Lindley distribution, the baseline distribution. However, the TLET-Lindley distribution provides the most consistent distribution for the datasets because it provides the lowest values of Akaike’s Information Criterion (AIC) and Bayesian Information Criterion (BIC). Moreover, the Kolmogorov-Smirnov tests are found to give high p-values.
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