[Statlist] Research seminar in statistics November 28th 2014, GSEM, University of Geneva

[Eva Cantoni]

Organisers :
E. Cantoni - E. Ronchetti - S. Sperlich - M-P. Victoria-Feser

Friday November 28th, 2014
at 11h15 - Room M 5220, Uni Mail (40, bd du Pont-d'Arve)


Alastair YOUNG
Imperial College, London


TITLE: Comparing analytic and simulation approaches to parametric inference

Abstract:
Two routes most commonly proposed for accurate inference on a scalar 
interest parameter in the presence of a (possibly high-dimensional) 
nuisance parameter are parametric simulation (`bootstrap') methods, and 
analytic procedures based on normal approximation to adjusted forms of 
the signed root likelihood ratio statistic. Both methods yield 
higher-order accuracy, in the sense that, under some null hypothesis of 
interest, p-values are uniformly distributed to error of third-order in 
the available sample size. But, given a specific inference problem, what 
is the formal relationship between p-values calculated by the two 
approaches? We elucidate the extent to which the two methodologies 
actually give the same inference.


Visit the website: http://www.stat-center.unige.ch/ressem.html

-- 
Prof. Eva Cantoni
Research Center for Statistics and
      Geneva School of Economics and Management
University of Geneva, Bd du Pont d'Arve 40, CH-1211 Genève 4
http://stat-center.unige.ch/members2/profs/eva-cantoni/