A Generic Sure Independence Screening Procedure
نویسندگان
چکیده
منابع مشابه
Sure Independence Screening
Big data is ubiquitous in various fields of sciences, engineering, medicine, social sciences, and humanities. It is often accompanied by a large number of variables and features. While adding much greater flexibility to modeling with enriched feature space, ultra-high dimensional data analysis poses fundamental challenges to scalable learning and inference with good statistical efficiency. Sure...
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Compressed sensing is a very powerful and popular tool for sparse recovery of high dimensional signals. Random sensing matrices are often employed in compressed sensing. In this paper we introduce a new method named aggressive betting using sure independence screening for sparse noiseless signal recovery. The proposal exploits the randomness structure of random sensing matrices to greatly boost...
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Ultrahigh dimensional variable selection plays an increasingly important role in contemporary scientific discoveries and statistical research. A simple and effective method is the correlation screening. For generalized linear models, we propose a more general version of the independent learning with ranking the maximum marginal likelihood estimates or the maximum marginal likelihood itself. We ...
متن کاملA discussion on “ Sure independence screening for ultrahigh di - mensional
mensional feature space” by J. Fan and L. Lv, Christian P. Robert, CEREMADE, Université Paris Dauphine and CREST, INSEE While I appreciate the “tour de force” involved in the paper, including the proof that P(M? ⊂ Mγ) converges, I cannot but get an overall feeling of slight disbelief about the statistical consequences of the results contained in the paper: in short, I basically question the per...
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Statistical inference can be computationally prohibitive in ultrahigh-dimensional linear models. Correlation-based variable screening, in which one leverages marginal correlations for removal of irrelevant variables from the model prior to statistical inference, can be used to overcome this challenge. Prior works on correlation-based variable screening either impose strong statistical priors on...
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ژورنال
عنوان ژورنال: Journal of the American Statistical Association
سال: 2018
ISSN: 0162-1459,1537-274X
DOI: 10.1080/01621459.2018.1462709