A novel asymmetric extension of power XLindley distribution: properties, inference and applications to engineering data

Abstract It is impossible to overstate the importance of using trigonometric functions appropriately in distribution theory. The main contribution of the research is to construct a flexible trigonometric extension of the power XLindley distribution. More specifically, we build an innovative two-parameter lifetime distribution known as the sine power XLindley distribution (SPXLD) using characteristics from the sine-generated family of distributions. As the main motivational fact, it provides an attractive alternative to the power Lindley, power XLindley, weighted Lindley, and extended power Lindley distributions; it may be better able to model lifetime phenomena presenting data of leptokurtic and platkurtic nature. In contrast to the increasing, decreasing, and reversed-j-shaped hazard rate function, the density exhibits asymmetric shapes with varying peakedness levels. Several significant characteristics are illustrated, including moments, the quantile function, the probability density function in series representation, the stress-strength reliability, and incomplete moments. To analyze the behavior of the suggested distribution, sixteen estimation techniques are applied, such as the maximum likelihood, percentiles, some methods of minimum distances, some methods based on minimum and maximum spacing distances, and the Kolmogorov method. After that, an extensive simulation study and the examination of two survival real datasets are used to show the viability, usefulness, and adaptability of the SPXLD. Relevant goodness of fit criteria demonstrates that the SPXLD fits several current distributions.

Authors

Publication Details

Journal
Physica Scripta
Published
2024-09-06
DOI
https://doi.org/10.1088/1402-4896/ad77fa
Citations
8
Primary Topic
Statistical Distribution Estimation and Applications
Type
article
Field-Weighted Citation Impact
5.67

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article

A novel asymmetric extension of power XLindley distribution: properties, inference and applications to engineering data

Mohammed Elgarhy, Amal Soliman Hassan, Najwan Alsadat, Vasili B V Nagarjuna et al.
8 citations
Physica Scripta
Statistical Distribution Estimation and Applications
5.67
article

A novel asymmetric extension of power XLindley distribution: properties, inference and applications to engineering data

Mohammed Elgarhy, Amal Soliman Hassan, Najwan Alsadat, Vasili B V Nagarjuna, Ahmed M. Gemeay, Sid Ahmed Benchiha
article en
8 citations

Abstract

Abstract It is impossible to overstate the importance of using trigonometric functions appropriately in distribution theory. The main contribution of the research is to construct a flexible trigonometric extension of the power XLindley distribution. More specifically, we build an innovative two-parameter lifetime distribution known as the sine power XLindley distribution (SPXLD) using characteristics from the sine-generated family of distributions. As the main motivational fact, it provides an attractive alternative to the power Lindley, power XLindley, weighted Lindley, and extended power Lindley distributions; it may be better able to model lifetime phenomena presenting data of leptokurtic and platkurtic nature. In contrast to the increasing, decreasing, and reversed-j-shaped hazard rate function, the density exhibits asymmetric shapes with varying peakedness levels. Several significant characteristics are illustrated, including moments, the quantile function, the probability density function in series representation, the stress-strength reliability, and incomplete moments. To analyze the behavior of the suggested distribution, sixteen estimation techniques are applied, such as the maximum likelihood, percentiles, some methods of minimum distances, some methods based on minimum and maximum spacing distances, and the Kolmogorov method. After that, an extensive simulation study and the examination of two survival real datasets are used to show the viability, usefulness, and adaptability of the SPXLD. Relevant goodness of fit criteria demonstrates that the SPXLD fits several current distributions.

Physica ScriptaVol. 99(10)
Deanship of Scientific Research, King Saud University
Openalex Percentile: Top 3%
Statistical Distribution Estimation and Applications
5.67
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