Abstract
In this paper, as an extension of Wrapping Lindley Distribution (WLD), we suggest a new circular distribution called the Wrapping Quasi Lindley Distribution (WQLD). We obtain the probability density function and derive the formula of a cumulative distribution function, characteristic function, trigonometric moments, and some related parameters for this WQLD. The maximum likelihood estimation method is used for the estimation of parameters.
Highlights
Directional data have many new and individual characteristics and tasks in modelling statistical analysis
Joshi and Jose [7] introduced the wrapped Lindley distribution, and they studied the properties of the new distribution, such as characteristic function and trigonometric moments
As an extension of the Wrapping Lindley Distribution (WLD), we suggest a new circular distribution called the Wrapping Quasi Lindley Distribution (WQLD)
Summary
Directional data have many new and individual characteristics and tasks in modelling statistical analysis. Joshi and Jose [7] introduced the wrapped Lindley distribution, and they studied the properties of the new distribution, such as characteristic function and trigonometric moments. While the wrapped Lindley distribution was introduced by Joshi and Jose (2018) [11] They defined the PDF and the CDF of the wrapped LD, respectively, as follows:. Ghitany et al [13] established many properties of LD and proved that the LD was a better model than the exponential distribution in many ways by using a real data set. They utilized the method of maximum likelihood to provide evidence that the fit of the Lindley distribution was better.
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