基于十分位数的总体分布均值的一个改进鲁棒置信区间

Q4 Mathematics

Statistics in Transition Pub Date : 2022-03-01 DOI:10.2478/stattrans-2022-0007

M. Abu-Shawiesh, Juthaphorn Sinsomboonthong, B. M. G. Kibria

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引用次数: 1

摘要

置信区间是种群位置和离散参数的一个重要统计估计量。本文考虑了一个稳健的修正置信区间，它是基于十分位数均值和十分位数标准差对Student t置信区间的调整，用于估计偏斜分布的总体均值。在广泛的蒙特卡罗模拟研究的基础上，对所提出的区间估计器的效率进行了评估。将所提出的置信区间的覆盖率和平均宽度与某些现有的和广泛使用的置信区间进行比较。仿真结果表明，总体而言，所提出的区间估计器的性能是高效的。为了便于说明，分析了三个真实生活中的数据集，这些数据集在一定程度上支持了模拟研究的结果。因此，当数据由正态分布或偏态分布生成时，我们建议从业者使用稳健的修正置信区间来估计总体平均值。

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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A modified robust confidence interval for the population mean of distribution based on deciles

Abstract The confidence interval is an important statistical estimator of population location and dispersion parameters. The paper considers a robust modified confidence interval, which is an adjustment of the Student’s t confidence interval based on the decile mean and decile standard deviation for estimating the population mean of a skewed distribution. The efficiency of the proposed interval estimator is evaluated on the basis of an extensive Monte Carlo simulation study. The coverage ratio and average width of the proposed confidence interval are compared with certain existing and widely used confidence intervals. The simulation results show that, in general, the proposed interval estimator’s performance is highly effective. For illustrative purposes, three real-life data sets are analyzed, which, to a certain extent, support the findings obtained from the simulation study. Thus, we recommend that practitioners use the robust modified confidence interval for estimating the population mean when the data are generated by a normal or skewed distribution.

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来源期刊

Statistics in Transition Decision Sciences-Statistics, Probability and Uncertainty

CiteScore

1.00

自引率

0.00%

发文量

审稿时长

9 weeks

期刊介绍： Statistics in Transition (SiT) is an international journal published jointly by the Polish Statistical Association (PTS) and the Central Statistical Office of Poland (CSO/GUS), which sponsors this publication. Launched in 1993, it was issued twice a year until 2006; since then it appears - under a slightly changed title, Statistics in Transition new series - three times a year; and after 2013 as a regular quarterly journal." The journal provides a forum for exchange of ideas and experience amongst members of international community of statisticians, data producers and users, including researchers, teachers, policy makers and the general public. Its initially dominating focus on statistical issues pertinent to transition from centrally planned to a market-oriented economy has gradually been extended to embracing statistical problems related to development and modernization of the system of public (official) statistics, in general.