Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Large dimension forecasting models and random singular value spectra   We present a general method to detect and extract from a finite time sample
statistically meaningful correlations between input and output variables of
large dimensionality. Our central result is derived from the theory of free
random matrices, and gives an explicit expression for the interval where
singular values are expected in the absence of any true correlations between
the variables under study. Our result can be seen as the natural generalization
of the Marcenko-Pastur distribution for the case of rectangular correlation
matrices. We illustrate the interest of our method on a set of macroeconomic
time series.

23
The categories of this paper are: solv-int
2
The categories of this paper are: math
9
The categories of this paper are: nlin
19
The categories of this paper are: eess
15
The categories of this paper are: nucl-ex
20
The categories of this paper are: acc-phys
37
The categories of this paper are: supr-con
8
The categories of this paper are: hep-ex
16
The categories of this paper are: stat
27
The categories of this paper are: comp-gas
14
The categories of this paper are: math-ph
13
The categories of this paper are: quant-ph
36
The categories of this paper are: cmp-lg
30
The categories of this paper are: q-alg
26
The categories of this paper are: bayes-an
28
The categories of this paper are: alg-geom