期刊文献+

Theorem of Logarithm Expectation and Its Application to Prove Sample Correlation Coefficient as Unbiased Estimate

Theorem of Logarithm Expectation and Its Application to Prove Sample Correlation Coefficient as Unbiased Estimate
下载PDF
导出
摘要 In statistical theory, a statistic that is function of sample observations is used to estimate distribution parameter. This statistic is called unbiased estimate if its expectation is equal to theoretical parameter. Proving whether or not a statistic is unbiased estimate is very important but this proof may require a lot of efforts when statistic is complicated function. Therefore, this research facilitates this proof by proposing a theorem which states that the expectation of variable x 〉 0 is u if and only if the limit of logarithm expectation of x approaches logarithm of u. In order to make clear of this theorem, the research gives an example of proving correlation coefficient as unbiased estimate by taking advantages of this theorem.
作者 Loc Nguyen
出处 《Journal of Mathematics and System Science》 2014年第9期605-608,共4页 数学和系统科学(英文版)
关键词 Logarithm expectation correlation coefficient unbiased estimate 定理证明 无偏估计 相关系数 期望 对数 样本 应用 统计理论
  • 相关文献

参考文献4

  • 1Sean Borman. The Expectation Maximization Algorithm - A short tutorial. Department of Electrical Engineering, University of Notre Dame, South Bend, Indiana. Last updated January 09, 2009.
  • 2Douglas C. Montgomery, George C. Runger. Applied Statistics and Probability for Enginners, 3rd edition. Copyright 2003 John Wiley & Son, Inc, 2003. ISBN: 0-471-20454-4.
  • 3Jeff A. Bilmes. A Gentle Tutorial of the EM Algorithm and its Application to Parameter Estimation for Gaussian Mixture and Hidden Markov Models. International Computer Science Institute, Berkeley CA, 94704 and Computer Science Division, Department of Electrical Engineering and Computer Science, U.C. Berkeley, TR-97-021, April 1998.
  • 4Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers, Keying Ye. Probability & Statistics for Engineers & Scientists, 9th edition. Copyright 2012, 2007, 2002 Pearson Education, Inc. ISBN: 978-0-321-62911-1.

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部