Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Joint estimation of $K$ related regression models with simple $L_1$-norm
  penalties   We propose a new approach, along with refinements, based on $L_1$ penalties
and aimed at jointly estimating several related regression models. Its main
interest is that it can be rewritten as a weighted lasso on a simple
transformation of the original data set. In particular, it does not need new
dedicated algorithms and is ready to implement under a variety of regression
models, {\em e.g.}, using standard R packages. Moreover, asymptotic oracle
properties are derived along with preliminary non-asymptotic results,
suggesting good theoretical properties. Our approach is further compared with
state-of-the-art competitors under various settings on synthetic data: these
empirical results confirm that our approach performs at least similarly to its
competitors. As a final illustration, an analysis of road safety data is
provided.

12
The categories of this paper are: nucl-th
11
The categories of this paper are: hep-lat
17
The categories of this paper are: q-fin
27
The categories of this paper are: comp-gas
24
The categories of this paper are: dg-ga
37
The categories of this paper are: supr-con
35
The categories of this paper are: mtrl-th
28
The categories of this paper are: alg-geom
4
The categories of this paper are: cond-mat
26
The categories of this paper are: bayes-an
29
The categories of this paper are: funct-an
14
The categories of this paper are: math-ph
25
The categories of this paper are: patt-sol
2
The categories of this paper are: math
15
The categories of this paper are: nucl-ex
20
The categories of this paper are: acc-phys