Reparametrization of the least favorable submodel in semi-parametric multisample models
Statistics Theory
2012-05-10 v1 Statistics Theory
Abstract
The method of estimation in Scott and Wild (Biometrika 84 (1997) 57--71 and J. Statist. Plann. Inference 96 (2001) 3--27) uses a reparametrization of the profile likelihood that often reduces the computation times dramatically. Showing the efficiency of estimators for this method has been a challenging problem. In this paper, we try to solve the problem by investigating conditions under which the efficient score function and the efficient information matrix can be expressed in terms of the parameters in the reparametrized model.
Keywords
Cite
@article{arxiv.1205.1920,
title = {Reparametrization of the least favorable submodel in semi-parametric multisample models},
author = {Yuichi Hirose and Alan Lee},
journal= {arXiv preprint arXiv:1205.1920},
year = {2012}
}
Comments
Published in at http://dx.doi.org/10.3150/10-BEJ342 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm)