基于最大熵原理，针对目前对混交林测树因子概率分布模型研究的不足，提出了联合最大熵概率密度函数，该函数具有如下特点：1）函数的每一组成部分都是相互联系的最大熵函数，故可以综合混交林各主要组成树种测树因子的概率分布信息；2）函数是具有双权重的概率表达式，能体现混交林结构复杂的特点，在最大限度地利用混交林每一主要树种测树因子概率分布信息的同时，还能精确地全面反映混交林测树因子概率分布规律；3）函数的结构简洁、性能优良.用天目山自然保护区的混交林样地对混交林测树因子概率分布模型进行了应用与检验，结果表明：模型的拟合精度(R2=0.9655)与检验精度(R2=
0.9772)都较高.说明联合最大熵概率密度函数可以作为混交林测树因子概率分布模型，为全面了解混交林林分结构提供了一种可行的方法.
Aiming at the deficiencies in the researches about the probability distribution model for mixed forests tree measurement factors, a joint maximum entr
opy probability density function was put forward, based on the maximum entropy principle. This function had the characteristics of 1) each element of the function was linked to the maximum entropy function, and hence, could integrate the information about the probability distribution of measurement factors of main tree species in mixed forests, 2) the function had a probability expression of doubleweight, being possible to reflect the characteristics of the complex structure of mixed forests, and accurately and completely reflect the probability distribution of tree measurement factors of mixed forests based on the fully use of the information about the probability distribution of measurement factors of main tree species in mixed forests, and 3) the joint maximum entropy probability density function was succinct in structure and excellent in performance. The model was applied and tested in two sampling plots in Tianmu Mountain Nature Reserve. The fitting precision (R2=0.9655) and testing accuracy (R2=0.9772) were both high, suggesting that this model could be used as a probability distribution model for mixed forests tree measurement factors, and provided a feasible method to fully understand the comprehensive structure of mixed forests.