Parameter Estimation in a Three-Parameter Lognormal Distribution
- 作者: Kozlov V.D.1, Maysuradze A.I.1
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隶属关系:
- Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University
- 期: 卷 30, 编号 3 (2019)
- 页面: 302-310
- 栏目: Article
- URL: https://journals.rcsi.science/1046-283X/article/view/247908
- DOI: https://doi.org/10.1007/s10598-019-09456-9
- ID: 247908
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详细
Point estimation methods for the three-parameter lognormal distribution are investigated and compared. The lognormal distribution is required in many topical areas, but so far there have been no comparative studies of the various estimation methods. We show that despite the large number of traditional estimation methods, the lognormal distribution requires special methods. We accordingly consider specializations of the main parameter estimation approaches, including the actively developing distance minimization methods. Their accuracy and speed are compared on simulated data. We show that specialized parameterestimation methods may outperform the highly popular maximum likelihood method.
作者简介
V. Kozlov
Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University
编辑信件的主要联系方式.
Email: kozlov.vld@mail.ru
俄罗斯联邦, Moscow
A. Maysuradze
Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University
Email: kozlov.vld@mail.ru
俄罗斯联邦, Moscow
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