王新洲. 在无偏估计类中改进最小二乘估计的方法[J]. 武汉大学学报 ( 信息科学版), 1995, 20(1): 46-50.
引用本文: 王新洲. 在无偏估计类中改进最小二乘估计的方法[J]. 武汉大学学报 ( 信息科学版), 1995, 20(1): 46-50.
Wang Xinzhou. The Method of Improving Least Square Estimate in Unbiased Estimation Class[J]. Geomatics and Information Science of Wuhan University, 1995, 20(1): 46-50.
Citation: Wang Xinzhou. The Method of Improving Least Square Estimate in Unbiased Estimation Class[J]. Geomatics and Information Science of Wuhan University, 1995, 20(1): 46-50.

在无偏估计类中改进最小二乘估计的方法

The Method of Improving Least Square Estimate in Unbiased Estimation Class

  • 摘要: 当平差模型中存在复共线关系时,未知参数的最小二乘估计很不可靠。提出了在无偏估计类中解决这一问题的有效方法——附加条件法,并从理论上证明了这一方法。

     

    Abstract: The least Square estimates are not reliable when there exists multicollinearity in adjustment model.To solve the problem statisticians improve least square estimates by biased estimates in biased estimation class.This paper presents an efficient method-Addition Restricted Condition Method(ARCM)-to solve the problem in unbiased estimation class,and proves that the method can improve least square estimates.

     

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