Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Improving Estimation in Functional Linear Regression with Points of
  Impact: Insights into Google AdWords   The functional linear regression model with points of impact is a recent
augmentation of the classical functional linear model with many practically
important applications. In this work, however, we demonstrate that the existing
data-driven procedure for estimating the parameters of this regression model
can be very instable and inaccurate. The tendency to omit relevant points of
impact is a particularly problematic aspect resulting in omitted-variable
biases. We explain the theoretical reason for this problem and propose a new
sequential estimation algorithm that leads to significantly improved estimation
results. Our estimation algorithm is compared with the existing estimation
procedure using an in-depth simulation study. The applicability is demonstrated
using data from Google AdWords, today's most important platform for online
advertisements. The \textsf{R}-package \texttt{FunRegPoI} and additional
\textsf{R}-codes are provided in the online supplementary material.

17
The categories of this paper are: q-fin
29
The categories of this paper are: funct-an
10
The categories of this paper are: q-bio
9
The categories of this paper are: nlin
12
The categories of this paper are: nucl-th
33
The categories of this paper are: plasm-ph
22
The categories of this paper are: chao-dyn
6
The categories of this paper are: astro-ph
24
The categories of this paper are: dg-ga
37
The categories of this paper are: supr-con
30
The categories of this paper are: q-alg
7
The categories of this paper are: hep-th
11
The categories of this paper are: hep-lat
32
The categories of this paper are: atom-ph
20
The categories of this paper are: acc-phys
21
The categories of this paper are: adap-org