Vladimir Panov, HSE University
Title: Mellin Transform Techniques for Statistical Inference
Abstract: My talk is devoted to the application of Mellin transform techniques to various statistical problems arising in the context of mixture models. For variance-mean mixtures, I will present a new semiparametric approach based on the properties of the superposition of Mellin and Laplace transforms. Later, I will show an adaptation of this method to more complicated models of moving average Levy processes, which is closely related to a wide (and rather popular) class of models known as the ambit fields. Also we will present some new theoretical facts concerning the Mellin transform (e.g., the analogue of the Berry-Esseen inequality), which yield some fresh ideas for the statistical estimation in the classical model of multiplicative mixtures.