Abstract
Regression analysis is a statistical process for estimating the relationships among variables based on probability. Because not all the imprecise quantities can be described by random variables, it is necessary to investigate relationships between an uncertain variable and some other variables. In this paper, an uncertain linear regression model is established based on uncertainty theory. Then, the estimators of parameters are obtained in the proposed model by the empirical uncertainty distribution coming from experts’ experimental data. Finally, the uncertain linear regression model is applied to solve an estimate problem.
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Acknowledgments
This work was supported by Hebei Natural Science Foundations (Nos. G2013402063 and F2012402037).
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Guo, H., Wang, X. & Gao, Z. Uncertain linear regression model and its application. J Intell Manuf 28, 559–564 (2017). https://doi.org/10.1007/s10845-014-1022-4
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DOI: https://doi.org/10.1007/s10845-014-1022-4