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http://dx.doi.org/10.5351/CSAM.2016.23.6.517

A comparison of inverse transform and composition methods of data simulation from the Lindley distribution  

Okwuokenye, Macaulay (Department of Biostatistics, Jiann-Ping Hsu College of Public Health, Georgia Southern University)
Peace, Karl E. (Department of Biostatistics, Jiann-Ping Hsu College of Public Health, Georgia Southern University)
Publication Information
Communications for Statistical Applications and Methods / v.23, no.6, 2016 , pp. 517-529 More about this Journal
Abstract
This study compares the inverse transform and the composition methods for generating data from the Lindley distribution. The expression for the inverse of the distribution function for the Lindley distribution does not exist in closed form. Hence, authors of many empirical studies on the Lindley distribution used methods for generating Lindley variates other than the inverse transform. We generated data from the Lindley distribution using the inverse transform approach by obtaining the Lindley variates numerically; we also generated data from this distribution using the composition approach. Following the generation of the Lindley variates using these two methods, we compare some statistical properties of the estimates of the Lindley model parameters based on the generated data. We conclude that the two methods produce similar results.
Keywords
Lindley distribution; simulation; inverse transform; composition; mixture density; weighted density; random variable; Lambert function;
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Times Cited By KSCI : 1  (Citation Analysis)
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