多元污染正态分布的线性判别误分率研究

ON THE MISCLASSIFICATION BY A LINEAR DISCRIMINATION OF A CONTAMINATED MULTI-VARIATE NORMAL DISTRIBUTION

  • 摘要: 本文研究了以下多元污染正态模型的线性判别,给出了两类条件误分率的渐近分布,以及无条件误分率: \Pi_i:(1-\alpha) N\left(\mu_i, \Sigma\right)+\alpha N\left(\mu_i, k^2 \Sigma\right), \quad i=1,2其中,α为污染率(0≤α≤1),∑,k2为尺度参数,而位置参数μ1,μ2可假定为未知,渐近分布及误分率的具体形式由定理1、定理2给出。

     

    Abstract: This paper discusses the linear discrimination of the following multi-variate normal model:\Pi_i:(1-\alpha) N\left(\mu_i, \Sigma\right)+\alpha N\left(\mu_i, k^2 \Sigma\right), \quad i=1,2 where, is the contamination rate (0≤α≤1), ∑, k2 the scale parameters, and the location parameters μ1,μ2 may be assumed unknown. It gives out the asymptotic distributions of two kinds of oonditional, and one kind of unoonditional misclassification rates. Please refer to Theorems 1 and 2 for the definite forms of the asymptotic distributions and the misclassification rates.

     

/

返回文章
返回