Qayoom Danish, Rather Aafaq A, Alsadat Najwan, Hussam Eslam, Gemeay Ahmed M
Symbiosis Statistical Institute, Symbiosis International (Deemed University), Pune, 411004, India.
Department of Quantitative Analysis, College of Business Administration, King Saud University, P.O. Box 71115, Riyadh, 11587, Saudi Arabia.
Heliyon. 2024 Sep 26;10(19):e38335. doi: 10.1016/j.heliyon.2024.e38335. eCollection 2024 Oct 15.
This paper presents a new probability distribution called the DUS Lindley distribution, created by applying the DUS transformation to the traditional Lindley distribution. The study provides an in-depth analysis of the distribution's statistical properties. These properties include a variety of statistical measures such as the probability density function, cumulative distribution function, failure rate, survival function, reverse hazard function, Mills ratio, mean residual life, mean past life, moments, conditional moments, characteristic function, order statistics, entropy measures, likelihood ratio test and Lorenz and Bonferroni curves. Parameter estimation is performed using several methods including weighted least squares, maximum likelihood estimation, Cramer-Von Mises estimation, least squares and Anderson-Darling estimation. The paper also explores the estimation of system reliability and evaluates the performance of maximum likelihood estimators through simulation studies across different sample sizes. Finally, the DUS Lindley distribution is applied to two real-world datasets, demonstrating a better fit than other well-known distributions.
本文提出了一种新的概率分布,称为DUS林德利分布,它是通过将DUS变换应用于传统林德利分布而创建的。该研究对该分布的统计特性进行了深入分析。这些特性包括各种统计量,如概率密度函数、累积分布函数、失效率、生存函数、反向危险函数、米尔斯比率、平均剩余寿命、平均过去寿命、矩、条件矩、特征函数、顺序统计量、熵测度、似然比检验以及洛伦兹曲线和邦费罗尼曲线。使用包括加权最小二乘法、最大似然估计、克拉默 - 冯·米塞斯估计、最小二乘法和安德森 - 达林估计在内的几种方法进行参数估计。本文还探讨了系统可靠性的估计,并通过对不同样本量的模拟研究评估了最大似然估计量的性能。最后,将DUS林德利分布应用于两个实际数据集,结果表明它比其他知名分布具有更好的拟合度。