Optimal M-estimation in high-dimensional regression
Optimal M-estimation in high-dimensional regression
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DOI：
10.1073/pnas.1307845110
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发表时间：
2013-09-03
影响因子：
11.1
通讯作者：
Yu, Bin
中科院分区：
文献类型：
--
作者：
Bean, Derek;Bickel, Peter J.;Yu, Bin
在高维统计的现代环境中，我们考虑了当假定误差分布已知时，使用M-估算物在回归中优化目标函数的经典问题。我们提出了一种算法来计算此最佳目标函数，以考虑问题的维度。尽管在设计矩阵的假设下实现了最佳性，但我们的分析揭示了依赖维度的目标功能的通常有趣的家族。
We consider, in the modern setting of high-dimensional statistics, the classic problem of optimizing the objective function in regression using M-estimates when the error distribution is assumed to be known. We propose an algorithm to compute this optimal objective function that takes into account the dimensionality of the problem. Although optimality is achieved under assumptions on the design matrix that will not always be satisfied, our analysis reveals generally interesting families of dimension-dependent objective functions.