摘要：In the present paper, we constructed an estimator of a delta contaminated mixing density function g(λ) of an intensity of the Poisson distribution. The estimator is based on an expansion of the continuous portion g(λ) of the unknown pdf over an overcomplete dictionary with the recovery of the coefficients obtained as the solution of an optimization problem with Lasso penalty. In order to apply Lasso technique in the, so called, prediction setting where it requires virtually no assumptions on the dictionary and, moreover, to ensure fast convergence of Lasso estimator, we use a novel formulation of the optimization problem based on the inversion of the dictionary elements.
