Uncertain linear regression model and its application

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• 作者：Haiying Guo ; Xiaosheng Wang ; Zhichao Gao
• 关键词：Uncertainty theory ; Uncertainty distribution ; Uncertain statistics ; Linear regression model
• 刊名：Journal of Intelligent Manufacturing
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：28
• 期：3
• 页码：559-564
• 全文大小：
• 刊物类别：Business and Economics
• 刊物主题：Production; Manufacturing, Machines, Tools; Control, Robotics, Mechatronics;
• 出版者：Springer US
• ISSN：1572-8145
• 卷排序：28

文摘

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.