Uncertain maximum likelihood estimation with application to uncertain regression analysis

Regression analysis is a mathematical tool to estimate the relationship between explanatory variables and response variable. This paper defines a likelihood function in the sense of uncertain measure to represent the likelihood of unknown parameters. Furthermore, the method of maximum likelihood est...

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Bibliographic Details
Published in:Soft computing (Berlin, Germany) Germany), 2020-07, Vol.24 (13), p.9351-9360
Main Authors: Lio, Waichon, Liu, Baoding
Format: Article
Language:English
Subjects:
Artificial Intelligence
Computational Intelligence
Control
Engineering
Foundations
Mathematical Logic and Foundations
Maximum likelihood estimation
Mechatronics
Parameter estimation
Parameter uncertainty
Regression analysis
Regression models
Robotics
Uncertainty analysis
Variables
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Summary:Regression analysis is a mathematical tool to estimate the relationship between explanatory variables and response variable. This paper defines a likelihood function in the sense of uncertain measure to represent the likelihood of unknown parameters. Furthermore, the method of maximum likelihood estimation is used for the parameter estimation of uncertain regression models, and the uncertainty distribution of the disturbance term is simultaneously calculated. Finally, some numerical examples are documented to illustrate the proposed method.
ISSN:1432-7643
1433-7479
DOI:10.1007/s00500-020-04951-3