Abstract
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.
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Acknowledgements
This work was supported by National Natural Science Foundation of China under Grant No. 61873329.
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Lio, W., Liu, B. Uncertain maximum likelihood estimation with application to uncertain regression analysis. Soft Comput 24, 9351–9360 (2020). https://doi.org/10.1007/s00500-020-04951-3
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DOI: https://doi.org/10.1007/s00500-020-04951-3