Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Significance testing for canonical correlation analysis in high
  dimensions   We consider the problem of testing for the presence of linear relationships
between large sets of random variables based on a post-selection inference
approach to canonical correlation analysis. The challenge is to adjust for the
selection of subsets of variables having linear combinations with maximal
sample correlation. To this end, we construct a stabilized one-step estimator
of the euclidean-norm of the canonical correlations maximized over subsets of
variables of pre-specified cardinality. This estimator is shown to be
consistent for its target parameter and asymptotically normal provided the
dimensions of the variables do not grow too quickly with sample size. We also
develop a greedy search algorithm to accurately compute the estimator, leading
to a computationally tractable omnibus test for the global null hypothesis that
there are no linear relationships between any subsets of variables having the
pre-specified cardinality. Further, we develop a confidence interval for the
target parameter that takes the variable selection into account.

34
The categories of this paper are: chem-ph
35
The categories of this paper are: mtrl-th
8
The categories of this paper are: hep-ex
13
The categories of this paper are: quant-ph
11
The categories of this paper are: hep-lat
33
The categories of this paper are: plasm-ph
19
The categories of this paper are: eess
23
The categories of this paper are: solv-int
12
The categories of this paper are: nucl-th
29
The categories of this paper are: funct-an
6
The categories of this paper are: astro-ph
2
The categories of this paper are: math
20
The categories of this paper are: acc-phys
22
The categories of this paper are: chao-dyn
0
The categories of this paper are: hep-ph
26
The categories of this paper are: bayes-an