关键词: 互为自因变量, 两条回归线, 对偶回归, 哑变量, 联立方程组, 多元回归

Abstract:

The dual regression method can be used to fit the mutual dependent variable models,however,the error structure relationship between the two variables must be provided in application,and this method is only applicable to the linear error-in-variable model in ForStat,which brings inconvenience to forestry modeling.Using the measured data of dominant height(H₀),mean height(H)and mean diameter at breast height(D)from 100 sample plots in Pinus koraiensis forests in northeastern China,this paper demonstrates two regression lines in fitting the H₀-H model and the H-D model.Two new methods are proposed by introducing dummy variables to distinguish two regression lines,followed by the use of nonlinear simultaneous equations with error-in-variables or multivariate nonlinear regression estimation method to estimate the parameters of mutual dependent variable models.These new methods are applicable not only to common linear models such as the H₀-H model,but also to nonlinear models such as the H-D model.

Key words: mutual dependent variable, two regression lines, dual regression, dummy variable, simultaneous equations, multivariate regression