Confidence regions for the multinomial parameter with small sample size

Djalil Chafai (1, 2) , Didier Concordet (1, 2)

1 UPTE - Physiopathologie et Toxicologie Expérimentales
2 IMT - Institut de Mathématiques de Toulouse UMR5219

Consider the observation of n iid realizations of an experiment with d>1 possible outcomes, which corresponds to a single observation of a multinomial distribution M(n,p) where p is an unknown discrete distribution on {1,...,d}. In many applications, the construction of a confidence region for p when n is small is crucial. This concrete challenging problem has a long history. It is well known that the confidence regions built from asymptotic statistics do not have good coverage when n is small. On the other hand, most available methods providing non-asymptotic regions with controlled coverage are limited to the binomial case d=2. In the present work, we propose a new method valid for any d>1. This method provides confidence regions with controlled coverage and small volume, and consists of the inversion of the "covering collection"' associated with level-sets of the likelihood. The behavior when d/n tends to infinity remains an interesting open problem beyond the scope of this work.

Mots clés: Confidence regions; small samples; multinomial distribution

Domaines: Calcul [stat.CO]

Djalil Chafai, Didier Concordet. Confidence regions for the multinomial parameter with small sample size. Journal of the American Statistical Association, 2009, 104 (487), pp.1071-1079. ⟨10.1198/jasa.2009.tm08152⟩. ⟨hal-00278790v3⟩