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Application of Path Analysis on Forestry Multivariate Linear Model Collinearity Analysis

Xu Hui

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Abstract

Taken height-diameter multiple linear model of Pinus kesiya var.langbianensis as an example,the collinearity in this model was analyzed by using path analysis method.Moreover,path analysis method was compared with other analysis methods such as correlation method and the method of condition index,tolerance and variance inflation factor.Study results showed that path analysis could determine both whether there were multicollinearity and the sources and intensity of multicollinearity.Compared with the commonly used methods of multicollinearity test,path analysis methods showed more advantages.

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What this paper is about

Taken height-diameter multiple linear model of Pinus kesiya var.langbianensis as an example,the collinearity in this model was analyzed by using path analysis method.Moreover,path analysis method was compared with other analysis methods such as correlation method and the method of condition index,tolerance and variance inflation factor.Study results showed that path analysis could determine both whether there were multicollinearity and the sources and intensity of multicollinearity.Compared with the commonly used methods of multicollinearity test,path analysis methods showed more advantages.

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Available abstract

Taken height-diameter multiple linear model of Pinus kesiya var.langbianensis as an example,the collinearity in this model was analyzed by using path analysis method.Moreover,path analysis method was compared with other analysis methods such as correlation method and the method of condition index,tolerance and variance inflation factor.Study results showed that path analysis could determine both whether there were multicollinearity and the sources and intensity of multicollinearity.Compared with the commonly used methods of multicollinearity test,path analysis methods showed more advantages.

Key concepts: Multicollinearity, Variance inflation factor, Collinearity, Path analysis (statistics), Statistics, Mathematics, Multivariate statistics, Linear model

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