activity
20142026
collaborators

6 papers

stat.ME2026

Priority-preserving augmentation of goodness-of-fit tests by conditional calibration

Roman Guchenko

An omnibus goodness-of-fit statistic can fail to exploit simple diagnostic evidence efficiently. For example, under a standard normal null, an exceptionally large observation is di…

stat.ME2026

Goodness of Fit Tests Based on Joint Densities of Multiple Sample Statistics

Roman Guchenko

We propose goodness-of-fit tests based on simulated confidence sets for joint distributions of multiple sample statistics, focusing on absolutely continuous null distributions with…

stat.AP2022

Statistical Modelling for Improving Efficiency of Online Advertising

Irina Scherbakova, Andrey Pepelyshev, Yuri Staroselskiy +2

Real-time bidding has transformed the digital advertising landscape, allowing companies to buy website advertising space in a matter of milliseconds in the time it takes a webpage…

stat.ME2016

Optimal discrimination designs for semi-parametric models

Holger Dette, Roman Guchenko, Viatcheslav Melas +1

Much of the work in the literature on optimal discrimination designs assumes that the models of interest are fully specified, apart from unknown parameters in some models. Recent w…

stat.CO2015

Efficient computation of Bayesian optimal discriminating designs

Holger Dette, Roman Guchenko, Viatcheslav B. Melas

An efficient algorithm for the determination of Bayesian optimal discriminating designs for competing regression models is developed, where the main focus is on models with general…

stat.ME2014

Bayesian T-optimal discriminating designs

Holger Dette, Viatcheslav B. Melas, Roman Guchenko

The problem of constructing Bayesian optimal discriminating designs for a class of regression models with respect to the T-optimality criterion introduced by Atkinson and Fedorov (…