Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Linear screening for high-dimensional computer experiments   In this paper we propose a linear variable screening method for computer
experiments when the number of input variables is larger than the number of
runs. This method uses a linear model to model the nonlinear data, and screens
the important variables by existing screening methods for linear models. When
the underlying simulator is nearly sparse, we prove that the linear screening
method is asymptotically valid under mild conditions. To improve the screening
accuracy, we also provide a two-stage procedure that uses different basis
functions in the linear model. The proposed methods are very simple and easy to
implement. Numerical results indicate that our methods outperform existing
model-free screening methods.

13
The categories of this paper are: quant-ph
7
The categories of this paper are: hep-th
9
The categories of this paper are: nlin
4
The categories of this paper are: cond-mat
23
The categories of this paper are: solv-int
17
The categories of this paper are: q-fin
22
The categories of this paper are: chao-dyn
1
The categories of this paper are: cs
12
The categories of this paper are: nucl-th
2
The categories of this paper are: math
32
The categories of this paper are: atom-ph
34
The categories of this paper are: chem-ph
3
The categories of this paper are: physics
21
The categories of this paper are: adap-org
0
The categories of this paper are: hep-ph
8
The categories of this paper are: hep-ex