The Geometry of Statistical Efficiency and Matrix Statistics

K.Gustafson

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The Geometry of Statistical Efficiency and Matrix Statistics

机译：统计效率和矩阵统计的几何

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We will place certain parts of the theory of statistical efficiency into the author's operator trigonometry (1967), thereby providing new geometrical understanding of statistical efficiency. Important earlier results of Bloomfield and Watson, Durbin and Kendall, Rao and Rao, will be so interpreted. For example, worse case relative least squares efficiency corresponds to and is achieved by the maximal turning antieigenvectors of the covariance matrix. Some little-known historical perspectives will also be exposed. The overall view will be emphasized.

机译：我们将统计效率理论的某些部分放入作者的算子三角函数（1967）中，从而提供对统计效率的新的几何理解。 Bloomfield和Watson，Durbin和Kendall，Rao和Rao的重要早期结果将得到解释。例如，在最坏的情况下，相对最小二乘效率对应于协方差矩阵的最大转向反特征向量并通过该协反矩阵实现。一些鲜为人知的历史观点也将被揭露。整体观点将得到强调。

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《Advances in decision sciences》 |2007年第4期|共16页
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K.Gustafson;
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The Geometry of Statistical Efficiency and Matrix Statistics

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