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Fitting Methods of Mutual Dependent Variable Models in Forestry

  • Weisheng ZENG
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  • Academy of Inventory and Planning,National Forestry and Grassland Administration,Beijing 100714,China

Received date: 2024-04-15

  Revised date: 2024-07-09

  Online published: 2025-04-18

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.

Cite this article

Weisheng ZENG . Fitting Methods of Mutual Dependent Variable Models in Forestry[J]. Forest and Grassland Resources Research, 2024 , 0(4) : 78 -83 . DOI: 10.13466/j.cnki.lczyyj.2024.04.009

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