摘要
文章针对自变量的系数和输出因变量是模糊数的模糊线性回归模型,引入模糊数的可能性均值和方差,构建模糊数的可能性均值-方差距离测度。借助于最小一乘法原理,给出了使得可能性均值-方差距离误差达到最小的回归系数估计值的线性规划模型。最后给出实例说明了方法的有效性和可行性。
Aiming at the fuzzy linear regression model whose coefficient of independent variable and output dependent vari- able are fuzzy numbers, this paper constructs fuzzy number＇s possibilistic mean-variance distance measurement. With the aid of the least absolute principle, the paper presents a linear programming model for the estimation of the regression coefficient with the minimum possibilistic mean-variance distance error. Finally the paper uses two examples of symmetric and asymmetric triangular fuzzy numbers to illustrate the effectiveness and feasibility of the proposed method.
出处
《统计与决策》
CSSCI
北大核心
2017年第22期33-35,共3页
Statistics & Decision
基金
中央高校基本科研业务费资助项目(2015B28014)
江苏省自然科学基金资助项目(BK20130242)
关键词
可能性均值
可能性方差
模糊线性回归模型
possibilistic mean
possibilistic variance
fuzzy linear regression model
