Interval shrinkage estimation of the parameter of exponential distribution in the presence of outliers under loss functions

Q4 Mathematics Statistics in Transition Pub Date : 2022-09-01 DOI:10.2478/stattrans-2022-0030
P. Nasiri
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Abstract

Abstract In this paper, we studied estimators based on an interval shrinkage with equal weights point shrinkage estimators for all individual target points ¯θ ∈ (θ0,θ1) for exponentially distributed observations in the presence of outliers drawn from a uniform distribution. Estimators obtained from both shrinkage and interval shrinkage were compared, showing that the estimators obtained via the interval shrinkage method perform better. Symmetric and asymmetric loss functions were also used to calculate the estimators. Finally, a numerical study and illustrative examples were provided to describe the results.
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损失函数下存在异常值时指数分布参数的区间收缩估计
摘要在本文中,我们研究了在均匀分布中存在异常值的情况下,指数分布观测的所有单个目标点θ∈(θ0,θ1)的基于等权区间收缩的点收缩估计量的估计量。比较了由收缩和区间收缩获得的估计量,表明通过区间收缩方法获得的估计值性能更好。对称和非对称损失函数也被用来计算估计量。最后,通过数值研究和实例说明了结果。
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来源期刊
Statistics in Transition
Statistics in Transition Decision Sciences-Statistics, Probability and Uncertainty
CiteScore
1.00
自引率
0.00%
发文量
0
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.
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