تقدير مَعْلَمَاْت توزيع كوماراسوامي – باريتو بواسون بإستعمال طريقتي المربّعات الصغرى والطريقة المعتَمّدة على النسب المئوية والمقارنة بينهما

I. Hashim, Abas Lafta
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Abstract

This study exhibits a new distribution based on Kumaraswamy- G Poisson's generalization. It shows how the cumulative distribution function (cdf) and the probability density function (pdf) of a new distribution are presented. It has been expected that the new distribution will be more flexible and appropriate than the base distribution, this can be achieved by adding new parameters. Some important properties were also presented, such as the survival function. Moreover, the method based on percentages and the method of least squares are proposed to estimate the parameters of the new distribution. A particular simulation is also conducted here for the purpose of evaluating the proposed estimation method, this is by using the mean square error (MSE) and the bias (BIAS). It has been concluded that the simulation experiments have shown that the method based on percentages and the method of least squares have proven its efficiency of the two estimation methods in estimating the parameters of the model, and by comparison, it was found out that the method based on percentages is the best, because the distribution is skewed and has a long tail towards the right and has at least (MSE) and (BIAS).
تقدير مَعْلَمَاْت توزيع كوماراسوامي – باريتو بواسون بإستعمال طريقتي المربّعات الصغرى والطريقة المعتَمّدة على النسب المئوية والمقارنة بينهما
本研究在Kumaraswamy- G Poisson概化的基础上展示了一个新的分布。它展示了如何表示新分布的累积分布函数(cdf)和概率密度函数(pdf)。预计新的分布将比基本分布更加灵活和适当,这可以通过增加新的参数来实现。并给出了一些重要的性质,如生存函数。此外,提出了基于百分比的方法和最小二乘法来估计新分布的参数。为了评估所提出的估计方法,这里还进行了一个特定的模拟,这是通过使用均方误差(MSE)和偏差(bias)。仿真实验表明,基于百分比的方法和基于最小二乘法的方法在估计模型参数方面证明了两种估计方法的有效性,并且通过比较,发现基于百分比的方法是最好的,因为分布偏斜且向右有长尾,并且具有最小的(MSE)和(BIAS)。
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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