Parameter Estimation in a Three-Parameter Lognormal Distribution

Autor:	V. D. Kozlov, Archil Maysuradze
Rok vydání:	2019
Předmět:	Computational Mathematics Estimation theory Maximum likelihood Simulated data Log-normal distribution Distance minimization Point estimation Estimation methods Algorithm Mathematics
Zdroj:	Computational Mathematics and Modeling. 30:302-310
ISSN:	1573-837X 1046-283X
DOI:	10.1007/s10598-019-09456-9
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::13dd45b712e74d7458f3115fc9884499 https://doi.org/10.1007/s10598-019-09456-9 Zobrazit plný text záznamu Full text from SpringerLink