Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Empirical likelihood test for high-dimensional two-sample model   A non parametric method based on the empirical likelihood is proposed for
detecting the change in the coefficients of high-dimensional linear model where
the number of model variables may increase as the sample size increases. This
amounts to testing the null hypothesis of no change against the alternative of
one change in the regression coefficients. Based on the theoretical asymptotic
behaviour of the empirical likelihood ratio statistic, we propose, for a fixed
design, a simpler test statistic, easier to use in practice. The asymptotic
normality of the proposed test statistic under the null hypothesis is proved, a
result which is different from the $\chi^2$ law for a model with a fixed
variable number. Under alternative hypothesis, the test statistic diverges. We
can then find the asymptotic confidence region for the difference of parameters
of the two phases. Some Monte-Carlo simulations study the behaviour of the
proposed test statistic.

33
The categories of this paper are: plasm-ph
19
The categories of this paper are: eess
9
The categories of this paper are: nlin
22
The categories of this paper are: chao-dyn
4
The categories of this paper are: cond-mat
0
The categories of this paper are: hep-ph
3
The categories of this paper are: physics
23
The categories of this paper are: solv-int
7
The categories of this paper are: hep-th
27
The categories of this paper are: comp-gas
21
The categories of this paper are: adap-org
30
The categories of this paper are: q-alg
24
The categories of this paper are: dg-ga
29
The categories of this paper are: funct-an
36
The categories of this paper are: cmp-lg
25
The categories of this paper are: patt-sol