Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Scalar-on-function local linear regression and beyond   Regressing a scalar response on a random function is nowadays a common
situation. In the nonparametric setting, this paper paves the way for making
the local linear regression based on a projection approach a prominent method
for solving this regression problem. Our asymptotic results demonstrate that
the functional local linear regression outperforms its functional local
constant counterpart. Beyond the estimation of the regression operator itself,
the local linear regression is also a useful tool for predicting the functional
derivative of the regression operator, a promising mathematical object on its
own. The local linear estimator of the functional derivative is shown to be
consistent. On simulated datasets we illustrate good finite sample properties
of both proposed methods. On a real data example of a single-functional index
model we indicate how the functional derivative of the regression operator
provides an original and fast, widely applicable estimating method.

20
The categories of this paper are: acc-phys
21
The categories of this paper are: adap-org
26
The categories of this paper are: bayes-an
0
The categories of this paper are: hep-ph
27
The categories of this paper are: comp-gas
30
The categories of this paper are: q-alg
4
The categories of this paper are: cond-mat
15
The categories of this paper are: nucl-ex
33
The categories of this paper are: plasm-ph
17
The categories of this paper are: q-fin
32
The categories of this paper are: atom-ph
23
The categories of this paper are: solv-int
36
The categories of this paper are: cmp-lg
18
The categories of this paper are: econ
29
The categories of this paper are: funct-an
6
The categories of this paper are: astro-ph