A Bayes Sampling Allocation Scheme for Stratified Finite Populations With Hyperbinomial Prior Distributions

When sampling is carried out independently for the K strata of a finite stratified dichotomous population (defectives vs. standard items), and the number Z_i of defectives per stratum sample is observed, the corresponding probability function for X = (X_i , …, x_K ) is the product of hypergeometric functions which depend on the sample sizes n_i , the stratum sizes N_i , and the number of defectives M_i in the stratum (i = 1, …, K). It is assumed that prior information is available about the M_i 's which can be expressed, by suitable choice of the parameters a_i and b_i , as the product of independent hyperbinomial functions.

In each stratum the cost per observation is a known constant. Using squared error loss function, the prior Bayes risk is found for the linear function of interest,

and the optimum allocation of sample sizes is found, the one for which the prior Bayes risk is minimum when the total sampling budget is fixed.     

基于三分法的IFS非隶属度函数确定方法

针对直觉模糊集(IFS)的非隶属度函数难以确定的问题,提出一种基于三分法的IFS非隶属度函数确定方法.首先,给出了确定IFS非隶属度函数的计算公式和非犹豫度指数的概念,规范了IFS非隶属度函数的确定方法,进而给出了非犹豫度指数的性质定理.其次,提出了基于三分法的IFS非隶属度函数的计算方法,给出了正规直觉模糊集的概念,证明了该方法确定的直觉模糊集是正规直觉模糊集.最后,以空袭目标识别的指标参数(飞行高度)实例,验证了方法的有效性.