Histogram selection in non Gaussian regression
We deal with the problem of choosing a piecewise constant estimator of a regression function mapping into . We consider a non Gaussian regression framework with deterministic design points, and we adopt the non asymptotic approach of model selection penalization developed by Birgé and Massart. Given a collection of partitions of , with possibly exponential complexity, and the corresponding collection of piecewise constant estimators, we propose a penalized least squares criterion which...