A note on robust hypothesis testing

  • Authors:

  • L. Devroye;L. Gyorfi;G. Lugosi

  • Affiliations:

  • Sch. of Comput. Sci., McGill Univ., Montreal, Que.;-;-

  • Venue:
  • IEEE Transactions on Information Theory
  • Year:
  • 2006

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Abstract

We introduce a simple new hypothesis testing procedure, which, based on an independent sample drawn from a certain density, detects which of k nominal densities is the true density closest to, under the total variation (L1) distance. We obtain a density-free uniform exponential bound for the probability of false detection