一种新的Pareto型分布估计方法的比较

IF 1.6 Q1 STATISTICS & PROBABILITY
A. S. Nik, A. Asgharzadeh, S. Nadarajah
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引用次数: 6

摘要

Bourguignon等人(2016)引入了一种新的帕累托型分布来对收入和可靠性数据进行建模。本文的目的是从频率论和贝叶斯的角度来估计这种分布的参数。最大似然估计、矩估计法、百分位估计、最小二乘和加权最小二乘估计以及间距估计的最大乘积被认为是频繁度估计。我们还考虑了未知参数的贝叶斯估计和相关的可信区间。贝叶斯估计是使用重要性抽样方法计算的。为了评估不同估计的性能,进行了蒙特卡罗模拟研究。为了便于说明,对一些真实生活中的数据集进行了分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparisons of Methods of Estimation for a New Pareto-type Distribution
Bourguignon et al. (2016) introduced a new Pareto-type distribution to model income and reliability data. The aim of this paper is to estimate the parameters of this distribution from both frequentist and Bayesian view points. The maximum likelihood estimates, method of moment estimates, percentile estimates, least square and weighted least square estimates and maximum product of spacing estimates are considered as frequentist estimates. We have also considered the Bayes estimates of the unknown parameters and the associated credible intervals. The Bayes estimates are computed using an importance sampling method. To evaluate the performance of the different estimates, a Monte Carlo simulation study is carried out. Some real life data sets have been analyzed for illustrative purposes.
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来源期刊
Statistica
Statistica STATISTICS & PROBABILITY-
CiteScore
1.70
自引率
0.00%
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10 weeks
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