基于长度偏倚截断Lomax分布的埃及北西奈省居民收入、支出和消费调查研究数据分析

A. Hassan, A. W. Shawki, H. Muhammed
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引用次数: 1

摘要

本文引入长度偏置截断Lomax分布作为截断Lomax分布的加权形式。研究了长度偏置截断Lomax分布的基本分布特征。在完整和ii型截尾数据的情况下,提供了最大似然法来估计总体参数。计算了模型参数的渐近置信区间。为了证明估计的模式,提供了一个样本生成算法,以及蒙特卡罗模拟分析。从仿真研究中可以看出,随着审查水平的提高,参数估计的均方误差在所有给定值下都减小。随着样本量的增加,参数估计的均方误差和平均长度减小。随着样本量的增加,估计越来越准确,表明其渐近无偏。此外,在所有情况下,均方误差随着样本量的增加而减小,表明参数的估计是一致的。采用医疗数据建模以及家庭收入、支出和消费调查(HIECS)数据中家庭教育支出占家庭总支出的百分比来显示新模型的重要性。与建议的分布相比,Kumaraswamy、beta、截断幂Lomax、截断Weibull和一个参数-beta分布表现较差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of Household Income, Expenditure and Consumption Survey Research Data for North Sinai Governorate in Egypt Using Length Biased Truncated Lomax Distribution
The length biased truncated Lomax distribution is introduced in this study as a weighted form of the truncated Lomax distribution. The length biased truncated Lomax distribution’s essential distributional features are investigated. In the case of complete and type-II censored data, the maximum likelihood method is provided for estimating population parameter. The model parameter asymptotic confidence interval is calculated. To demonstrate the pattern of the estimate, a sample generation algorithm is supplied, as well as a Monte Carlo simulation analysis. We can see from the simulation research that as the censoring level is increased, the mean squared error of parameter estimates decrease’s for all given values. With increasing sample size, the mean squared error and average length of parameter estimates decrease. The estimates get increasingly accurate as the sample size grows higher, suggesting that its asymptotically unbiased. Furthermore, in all cases, the mean squared error diminishes as the sample size grows, indicating that the estimates of parameter are consistent. Modelling to medical data and the percentage of household spending on education out of total household expenditure from the household income, expenditure and consumption survey (HIECS) data are used to show the importance of the new model. The Kumaraswamy, beta, truncated power Lomax, truncated Weibull, and one parameter-beta distributions perform poorly in comparison to the suggested distribution.
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