期刊名称：Sankhya. Series A, mathematical statistics and probability
印刷版ISSN：0976-836X
电子版ISSN：0976-8378
出版年度：2008
卷号：70
期号：01
页码：1-24
出版社：Indian Statistical Institute
摘要：We discuss the importance of sparsity in the context of nonparametric regres-
sion and covariance matrix estimation. We point to low manifold dimension
of the covariate vector as a possible important feature of sparsity, recall an
estimate of dimension due to Levina and Bickel (2005) and establish some
conjectures made in that paper.
