Weighted Prakaamy Distribution: Properties, Applications and Analysis

D. Vedavathi Saraja, C. Subramanian, N. Srinivasa Rao
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Abstract

The paper introduces a new probability distribution, which is weighted version of the Prakaamy distribution. The paper explores various statistical properties of the Weighted Prakaamy (WP)distribution including probability density function (PDF), cumulative distribution function (CDF), moments, moment generating function, characteristics function, reliability analysis, ordered statistics, maximum likelihood estimation of parameters, entropies, likelihood ratiotest, and Bonferroni and Lorenz curves. The paper uses simulations to evaluate the performance of maximum likelihood estimators. The authorsapply the WP distribution to various real-life data sets from fields of engineering and medical science. This empirical analysis aims to evaluate the performance of the distribution in modeling and predicting real-world phenomena. The paper suggests that WP distribution outperforms other probability distributions including Prakaamy distribution, Exponential distribution, Erlang Truncated Exponential distribution, Power Lindley distribution and Lindley distribution.
加权Prakaamy分布:性质、应用与分析
本文引入了一种新的概率分布,即加权的Prakaamy分布。本文探讨了加权Prakaamy (WP)分布的各种统计性质,包括概率密度函数(PDF)、累积分布函数(CDF)、矩、矩生成函数、特征函数、可靠性分析、有序统计、参数的最大似然估计、熵、似然比检验以及Bonferroni和Lorenz曲线。本文通过仿真来评价极大似然估计器的性能。作者将WP分布应用于来自工程和医学领域的各种实际数据集。本实证分析旨在评估分布在建模和预测现实世界现象中的性能。本文认为,WP分布优于Prakaamy分布、指数分布、Erlang截断指数分布、Power Lindley分布和Lindley分布。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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