Nonparametric regression estimation based on spatially inhomogeneous data: minimax global convergence rates and adaptivity
We consider the nonparametric regression estimation problem of recovering an unknown response function on the basis of spatially inhomogeneous data when the design points follow a known density with a finite number of well-separated zeros. In particular, we consider two different cases: when has zeros of a polynomial order and when has zeros of an exponential order. These two cases correspond to moderate and severe data losses, respectively. We obtain asymptotic (as the sample size increases)...