The Le Cam distance between density estimation, Poisson processes and Gaussian white noise

  • Kolyan Ray

    Leiden University, Netherlands
  • Johannes Schmidt-Hieber

    Leiden University, Netherlands

Abstract

It is well known that density estimation on the unit interval is asymptotically equivalent to a Gaussian white noise experiment, provided the densities have Hölder smoothness larger than 1/2 and are uniformly bounded away from zero. We derive matching lower and constructive upper bounds for the Le Cam deficiencies between these experiments, with explicit dependence on both the sample size and the size of the densities in the parameter space. As a consequence, we derive sharp conditions on how small the densities can be for asymptotic equivalence to hold. The related case of Poisson intensity estimation is also treated.

Cite this article

Kolyan Ray, Johannes Schmidt-Hieber, The Le Cam distance between density estimation, Poisson processes and Gaussian white noise. Math. Stat. Learn. 1 (2018), no. 2, pp. 101–170

DOI 10.4171/MSL/1-2-1