Abstract:

Probability distribution of key factors in forest mensuration was very important in the management practice. It is poor understand that main variables multi-distribution of forest mensuration in the forest ecology,the bivariate distribution model of main variables of forest mensuration was introduced in this paper.We build up a bivariate maximum entropy probability density function used bivariate unite entropy function,and simulating unitary maximum entropy function. This approach demonstrated it was bivariate and exponential distribution for many parameters. It will prompt through to combine with the radix of bivariate consecutive function dimension.We analyzed and contrasted a bivariate maximum entropy function and a bivariate Weibull distribution,and pointed out the former had wider flexibility. The bivariate S_BB function and the bivariate Beta function were introduced and the selection of S_BB function's initial value had been elaborated and also pointed out that the bivariate S_BB function could reflect the two random variables's correlation； bivariate maximum entropy probability density function,bivariate S_BB function and the bivariate Beta function respectively were used to measure the two-dimension information of diameter-age. The results indicated that the precision of the former two methods were very high,and the two methods could be suited to describe the joint distribution of the bamboo diameter-age,for bivariate maximum entropy： minimum variance was 9.976 77e-05,R²= 0.996 0,A.H. Колмогоров statistical quantity was 0.999 83,for bivariate S_BB function： minimum variance was 0.000 84,R²= 0.964 00,A.H. Колмогоров statistical quantity was 0.979 98. the precision of the bivariate Beta function was lowest,the selection of its initial value and the variable range transformation were further researched.

Key words: bivariate maximum entropy function, bivariate S_BB function, bivariate Beta function, diameter-age, forest mensuration