广东工业大学学报 ›› 2011, Vol. 28 ›› Issue (2): 66-68.

• 综合研究 • 上一篇    下一篇

随机向量的相关与独立

  

  1. 广东工业大学 应用数学学院,广东 广州 510643
  • 出版日期:2011-06-25 发布日期:2011-06-25
  • 作者简介:陈鹤峰(1973-),男,讲师,硕士,主要研究方向为数理统计、图像处理、算法设计与分析
  • 基金资助:

    广东工业大学青年基金资助项目(072040)

Un-correlativity and Independency of Normal Random Vectors(Variables)

  1. Faculty of Applied Mathematics, Guangdong University of Technology, Guangzhou 510643, China
  • Online:2011-06-25 Published:2011-06-25

摘要: 归纳了判断随机向量独立性和不相关的方法.这些方法简化了随机向量独立与不相关的判定.讨论了常见的误区及判别方法,并给出应用实例.对这些方法提出了扩充方向.

关键词: 随机向量;正态分布;相关;独立

Abstract: or uncorrelated random vectors have many good properties. It is not enough to determine the uncorrelativity or independency just by virtue of its definition and intuition. First, it summarized the methods of determining independence or uncorrelated random vectors. It is important to avoid judging errors. Then, some examples were given, based on these methods. Finally, the expansion of these methods was proposed.

Key words: random vectors; normal distribution; un-correlativity; independency

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