Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Statistical Inference on Transformation Models: a Self-induced Smoothing
  Approach   This paper deals with a general class of transformation models that contains
many important semiparametric regression models as special cases. It develops a
self-induced smoothing for the maximum rank correlation estimator, resulting in
simultaneous point and variance estimation. The self-induced smoothing does not
require bandwidth selection, yet provides the right amount of smoothness so
that the estimator is asymptotically normal with mean zero (unbiased) and
variance-covariance matrix consistently estimated by the usual sandwich-type
estimator. An iterative algorithm is given for the variance estimation and
shown to numerically converge to a consistent limiting variance estimator. The
approach is applied to a data set involving survival times of primary biliary
cirrhosis patients. Simulations results are reported, showing that the new
method performs well under a variety of scenarios.

8
The categories of this paper are: hep-ex
0
The categories of this paper are: hep-ph
30
The categories of this paper are: q-alg
7
The categories of this paper are: hep-th
26
The categories of this paper are: bayes-an
37
The categories of this paper are: supr-con
5
The categories of this paper are: gr-qc
13
The categories of this paper are: quant-ph
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
29
The categories of this paper are: funct-an
10
The categories of this paper are: q-bio
34
The categories of this paper are: chem-ph
19
The categories of this paper are: eess
20
The categories of this paper are: acc-phys