activity
20152025
most citedOptimal approximate designs for estimating treatment contrasts resistant to nuisance effects

10 citations · 18 across the 11 of their papers we have counts for

collaborators

14 papers

cs.SI2025

Laplacian Network Optimization via Information Functions

Samuel Rosa, Radoslav Harman

Designing networks to optimize robustness and other performance metrics is a well-established problem with applications ranging from electrical engineering to communication network…

stat.CO2025

Removal of Redundant Candidate Points for the Exact D-Optimal Design Problem

Radoslav Harman, Samuel Rosa

One of the most common problems in statistical experimentation is computing D-optimal designs on large finite candidate sets. While optimal approximate (i.e., infinite-sample) desi…

stat.CO2024

A Randomized Exchange Algorithm for Optimal Design of Multi-Response Experiments

Pál Somogyi, Samuel Rosa, Radoslav Harman

Despite the increasing prevalence of vector observations, computation of optimal experimental design for multi-response models has received limited attention. To address this probl…

stat.CO2023★ 1 cited

The Polytope of Optimal Approximate Designs: Extending the Selection of Informative Experiments

Radoslav Harman, Lenka Filová, Samuel Rosa

Consider the problem of constructing an experimental design, optimal for estimating parameters of a given statistical model with respect to a chosen criterion. To address this prob…

stat.CO2023★ 7 cited

Mixed-integer linear programming for computing optimal experimental designs

Radoslav Harman, Samuel Rosa

The problem of computing an exact experimental design that is optimal for the least-squares estimation of the parameters of a regression model is considered. We show that this prob…

stat.CO2021

Optimal Design of Multifactor Experiments via Grid Exploration

Radoslav Harman, Lenka Filová, Samuel Rosa

For computing efficient approximate designs of multifactor experiments, we propose a simple algorithm based on adaptive exploration of the grid of all combinations of factor levels…