Tailor-made tests for goodness of fit to semiparametric hypotheses

2006/07/01 by Peter J. Bickel, Ya'acov Ritov, Thomas M. Stoker · 1 citation
Mathematics · #math.ST #stat.TH #msc:62G10 #msc:62G20 #msc:62G09

paper · pdf · doi:10.1214/009053606000000137

published as Annals of Statistics 2006, Vol. 34, No. 2, 721-741 · Published at http://dx.doi.org/10.1214/009053606000000137 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)

arxiv created 2006/07/01 · arxiv updated 2009/12/01

Abstract

We introduce a new framework for constructing tests of general semiparametric hypotheses which have nontrivial power on the n^-1/2 scale in every direction, and can be tailored to put substantial power on alternatives of importance. The approach is based on combining test statistics based on stochastic processes of score statistics with bootstrap critical values.

Cited by

• Goodness-of-Fit Tests for Censored and Truncated Data: Maximum Mean Discrepancy Over Regular Functionals