摘要
研究单参数Pareto分布存在变点时的估计问题,分别利用极大似然估计法和贝叶斯方法对单参数Pareto分布的变点进行估计,并运用Matlab软件进行随机模拟,随机结果表明贝叶斯方法与极大似然估计相比,估计值更接近真值.
This paper studies the estimation problem when the single parameter Pareto distribution has change points.The maximum likelihood estimation method and the Bayesian method are used to estimate the change points of the single-parameter Pareto distribution,and the Matlab software is used for stochastic simulation.The results show that the Bayesian estimation compared with maximum likelihood estimation,the estimated value of the Bayesian method is closer to the true value.
作者
沙雪云
周菊玲
董翠玲
SHA Xue-yun;ZHOU Ju-ling;DONG Cui-ling(School of Mathematics and Science,Xinjiang Normal University,Urumqi 830017,China)
出处
《数学的实践与认识》
2021年第1期170-177,共8页
Mathematics in Practice and Theory
基金
国家自然科学基金青年项目(11801488)
新疆师范大学校级重点实验室招标课题(XJNUSYS2019B05)
新疆师范大学教改工程项目(SDJG2018-46)。
关键词
PARETO分布
变点
贝叶斯估计
极大似然估计
pareto distribution
change-point
the bayesian estimation
maximum likelihood estimation
