A note on density model size testing

Let (F/sub k/)/sub k/spl ges/1/ be a nested family of parametric classes of densities with finite Vapnik-Chervonenkis dimension. Let f be a probability density belonging to F/sub k//sup */, where k/sup */ is the unknown smallest integer such that f/spl isin/F/sub k/. Given a random sample X/sub 1/,...,X/sub n/ drawn from f, an integer k/sub 0//spl ges/1 and a real number /spl alpha//spl isin/(0,1), we introduce a new, simple, explicit /spl alpha/-level consistent testing procedure of the null hypothesis {H/sub 0/:k/sup */=k/sub 0/} versus the alternative {H/sub 1/:k/sup *//spl ne/k/sub 0/}. Our method is inspired by the combinatorial tools developed in Devroye and Lugosi and it includes a wide range of density models, such as mixture models, neural networks, or exponential families.