Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Model-Free Sure Screening via Maximum Correlation   We consider the problem of screening features in an ultrahigh-dimensional
setting. Using maximum correlation, we develop a novel procedure called MC-SIS
for feature screening, and show that MC-SIS possesses the sure screen property
without imposing model or distributional assumptions on the response and
predictor variables. Therefore, MC-SIS is a model-free sure independence
screening method as in contrast with some other existing model-based sure
independence screening methods in the literature. Simulation examples and a
real data application are used to demonstrate the performance of MC-SIS as well
as to compare MC-SIS with other existing sure screening methods. The results
show that MC-SIS outperforms those methods when their model assumptions are
violated, and it remains competitive when the model assumptions hold.

7
The categories of this paper are: hep-th
17
The categories of this paper are: q-fin
13
The categories of this paper are: quant-ph
9
The categories of this paper are: nlin
31
The categories of this paper are: ao-sci
22
The categories of this paper are: chao-dyn
0
The categories of this paper are: hep-ph
25
The categories of this paper are: patt-sol
12
The categories of this paper are: nucl-th
28
The categories of this paper are: alg-geom
36
The categories of this paper are: cmp-lg
26
The categories of this paper are: bayes-an
32
The categories of this paper are: atom-ph
20
The categories of this paper are: acc-phys
8
The categories of this paper are: hep-ex
5
The categories of this paper are: gr-qc