Allometric equation is the most extensively applied method for estimating aboveground biomass (AGB). However, most studies focus only on an equation establishment and its precision and ignore errors in coefficient. Hence, the current paper aims to address the heteroscedasticity limitations of linear regression, which is the most extensively used method for solving the coefficient of allometric equations. In this paper, we proposed weighed linear regression with new weighed factor for estimating AGB. At meantime, we compared this method with other two common methods, which are simple linear regression and nonlinear regression, through solving their coefficients, accuracy assessment, and biomass estimate which forward compared with the biomass of 71 trees associated with 4 species at Xiaolong Mountain in the Gansu province of China. The results showed that the precision of coefficients of power progress of weighted linear regression and nonlinear least square regression is very close, and higher than the linear regression.

   Keywords: Above ground biomass (AGP), allometric equation, linear regression, weighted linear regression, nonlinear regression