Orateur
Prof.
Béatrice Laurent
(IMT/INSA)
Description
We consider a d-dimensional i.i.d sample from a distribution with unknown density f. The problem of detection of a two-component mixture is considered. Our aim is to decide whether f is the density of a standard Gaussian random d-vector ($f=\phi_d$) against f is a two-component mixture: $f=(1−\varepsilon)\phi_{d}+\varepsilon \phi_{d}(.−\mu)$ where $(\varepsilon,\mu)$ are unknown parameters. Optimal separation conditions on $\varepsilon, \mu ,n$ and the dimension d are established, allowing to separate both hypotheses with prescribed errors. Several testing procedures are proposed and two alternative subsets are considered.
Work in collaboration with C. Marteau (ICJ) and Cathy Maugis-Rabusseau (IMT/INSA)
Author
Prof.
Béatrice Laurent
(IMT/INSA)
Co-auteurs
Dr
Cathy Maugis-Rabusseau
(IMT/INSA)
Prof.
Clément Marteau
(ICJ)
