Objective  Different crown prediction methods were used to predict varied crown components (east, west, south, north crown width and east-west crown width, south-north crown width, average crown width) of young spruce fir, and the prediction accuracy was compared in order to provide a theoretical basis for the tending of spruce fir management.

  Method  The measured data of different crown components in permanent spruce fir sample plots was got from three 1 ha sample plots on Jingouling Forest Farm of northeastern China in 2013, the logistic model was chosen as base model and the ordinary least square method was used to fit crown radii of east, west, south, north and crown width of east-west, south-north, and mean direction. 1/D, 1/D^0.5, and 1/D² were used as weight function to eliminate the heteroscedasticity of model residuals. The unweighted nonlinear seemingly unrelated regression method, weighted nonlinear seemingly unrelated regression method, quantile regression method, and ordinary least square method were applied to develop different crown component prediction model.

  Result  The fitting results indicated that, quantile regression model had the lowest fitting accuracy, compared with quantile regression, weighted nonlinear seemingly unrelated regression and weighted ordinary least square regression had nearly same fitting effectiveness. The accuracy order arrangement was weighted NSUR ≈ weighted OLS > OLS > QR, 1/D² was the best choice to eliminate heteroscedasticity by residuals plot.

  Conclusion  In this paper, the fitting effect of nonlinear quantile regression model was not necessarily better than that of nonlinear least square method, the weighted nonlinear seemingly unrelated regression model (1/D² as weight function) developed in this essay can provide some theory basis for different crown components of young spruce fir.