Achieving the oracle property of OEM with nonconvex penalties

Statistical Theory and Related Fields(2017)

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摘要
Thepenalised least square estimator of non-convex penalties such as the smoothly clipped absolute deviation (SCAD) and the minimax concave penalty (MCP) is highly nonlinear and has many local optima. Finding a local solution to achieve the so-called oracle property is a challenging problem. We show that the orthogonalising EM (OEM) algorithm can indeed find such a local solution with the oracle property under some regularity conditions for a moderate but diverging number of variables.
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关键词
em algorithm,non-convex optimisation,penalised regression,variable selection
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