【摘 要】
：
Estimating a large precision (inverse covariance) matrix is diffcult due to the curse of dimensionality.The sample covariance matrix is notoriously bad for
【机 构】
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Department of Statistics London School of Economics and Political Science
【出 处】
：
2009 International Conference on Financial Statistics and Fi
论文部分内容阅读
Estimating a large precision (inverse covariance) matrix is diffcult due to the curse of dimensionality.The sample covariance matrix is notoriously bad for estimating the covariance matrix when the dimension p of the multivariate vector is comparable or even larger than the number of time points n observed.It is singular and hence cannot be inverted for the precision matrix.
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