【摘 要】
：
Consider a linear regression model Y =Xβ + z, z ~ N(0.In), X =Xn,p,where both p and n are large but p > n.The vector β is unknown but is sparse in the sen
【机 构】
：
CarnegieMellonUniversityDepartmentofStatistics,BakerHallCarnegieMellonUniversity,Pittsburgh,PA15217
【出 处】
：
The Third IMS-China International Conference on Statistics a
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Consider a linear regression model Y =Xβ + z, z ~ N(0.In), X =Xn,p,where both p and n are large but p > n.The vector β is unknown but is sparse in the sense that only a small proportion of its coordinates is nonzero, and we are interested in identifying these nonzero ones.We model the coordinates of β as samples from a two-component mixture (1-)vo + π, and the rows of X as samples from N(0, 1/nΩ), where vo is the point mass at 0, π is a distribution, and Ω is a p by p correlation matrix which is unknown but is presumably sparse.
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