Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Score estimation in the monotone single index model   We consider estimation in the single index model where the link function is
monotone. For this model a profile least squares estimator has been proposed to
estimate the unknown link function and index. Although it is natural to propose
this procedure, it is still unknown whether it produces index estimates which
converge at the parametric rate. We show that this holds if we solve a score
equation corresponding to this least squares problem. Using a Lagrangian
formulation, we show how one can solve this score equation without any
reparametrization. This makes it easy to solve the score equations in high
dimensions. We also compare our method with the Effective Dimension Reduction
(EDR) and the Penalized Least Squares Estimator (PLSE) methods, both available
on CRAN as R packages, and compare with link-free methods, where the covariates
are ellipticallly symmetric.

27
The categories of this paper are: comp-gas
20
The categories of this paper are: acc-phys
29
The categories of this paper are: funct-an
0
The categories of this paper are: hep-ph
14
The categories of this paper are: math-ph
18
The categories of this paper are: econ
23
The categories of this paper are: solv-int
28
The categories of this paper are: alg-geom
1
The categories of this paper are: cs
26
The categories of this paper are: bayes-an
3
The categories of this paper are: physics
15
The categories of this paper are: nucl-ex
35
The categories of this paper are: mtrl-th
4
The categories of this paper are: cond-mat
11
The categories of this paper are: hep-lat
22
The categories of this paper are: chao-dyn