Abstract:

The paper described the evolvement of home and abroad in modeling dominant height using nonlinear mixed effect models. The nonlinear mixed effect model of dominant height related with forest age was developed by changing the number of random effect parameter of Richards and Logistic growth model based on the data of Chinese Fir plantation of different initial planting density in Dagangshan Experiment Bureau of Jiangxi Province. The simulation’s precision of different models was compared with coefficient of determination, mean square error and absolute bias. The results showed that the precision of nonlinear mixed effect model which takes into account the random effect of different initial planting density was better than that of conventional regression model. But increasing the number of random effect parameter was not absolutely able to increase the simulation’s precision of model, on the contrary the precision may decrease possibly. The simulation’s precision of Logistics including three random effect parameter based on the fourth equation was maximal.

Key words: Chinese Fir (Cunninghamia lanceolata), nonlinear mixed effect model, dominant height, Richards, Logistic