Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Functional principal components analysis via penalized rank one
  approximation   Two existing approaches to functional principal components analysis (FPCA)
are due to Rice and Silverman (1991) and Silverman (1996), both based on
maximizing variance but introducing penalization in different ways. In this
article we propose an alternative approach to FPCA using penalized rank one
approximation to the data matrix. Our contributions are four-fold: (1) by
considering invariance under scale transformation of the measurements, the new
formulation sheds light on how regularization should be performed for FPCA and
suggests an efficient power algorithm for computation; (2) it naturally
incorporates spline smoothing of discretized functional data; (3) the
connection with smoothing splines also facilitates construction of
cross-validation or generalized cross-validation criteria for smoothing
parameter selection that allows efficient computation; (4) different smoothing
parameters are permitted for different FPCs. The methodology is illustrated
with a real data example and a simulation.

25
The categories of this paper are: patt-sol
20
The categories of this paper are: acc-phys
36
The categories of this paper are: cmp-lg
4
The categories of this paper are: cond-mat
11
The categories of this paper are: hep-lat
26
The categories of this paper are: bayes-an
12
The categories of this paper are: nucl-th
8
The categories of this paper are: hep-ex
18
The categories of this paper are: econ
15
The categories of this paper are: nucl-ex
23
The categories of this paper are: solv-int
32
The categories of this paper are: atom-ph
3
The categories of this paper are: physics
10
The categories of this paper are: q-bio
28
The categories of this paper are: alg-geom
5
The categories of this paper are: gr-qc