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While optimal input design for linear systems has been well-established, no systematic approach exists for nonlinear systems where robustness to extrapolation/interpolation errors is prioritized over minimizing estimated parameter variance.…

Systems and Control · Electrical Eng. & Systems 2025-05-09 Yuhan Liu , Máté Kiss , Roland Tóth , Maarten Schoukens

In this paper, we further investigate the problem of selecting a set of design points for universal kriging, which is a widely used technique for spatial data analysis. Our goal is to select the design points in order to make simultaneous…

Methodology · Statistics 2024-01-18 Helmut Waldl , Werner G. Müller , Paula Camelia Trandafir

Design-based simulations - procedures that hold realized outcomes fixed and generate variation by resampling treatment assignment or shocks - are widely used in both methodological and applied work to assess inference procedures. This paper…

Econometrics · Economics 2026-03-13 Bruno Ferman

Computer experiments have become ubiquitous in science and engineering. Commonly, runs of these simulations demand considerable time and computing, making experimental design extremely important in gaining high quality information with…

Statistics Theory · Mathematics 2017-05-15 Benjamin Haaland , Wenjia Wang , Vaibhav Maheshwari

In a group testing scheme, a set of tests is designed to identify a small number $t$ of defective items that are present among a large number $N$ of items. Each test takes as input a group of items and produces a binary output indicating…

Information Theory · Computer Science 2016-11-17 Arya Mazumdar

Context: Software engineering is becoming more and more distributed. Developers and other stakeholders are often located in different locations, departments, and countries and operating within different time zones. Most online software…

Software Engineering · Computer Science 2023-11-30 Martin Stancek , Ivan Polasek , Tibor Zalabai , Juraj Vincur , Rodi Jolak , Michel Chaudron

We introduce statistical techniques required to handle complex computer models with potential applications to astronomy. Computer experiments play a critical role in almost all fields of scientific research and engineering. These computer…

Instrumentation and Methods for Astrophysics · Physics 2021-09-01 Joshua Lukemire , Qian Xiao , Abhyuday Mandal , Weng Kee Wong

Orthogonal Graph Representations are essential tools for testing existence of hidden variables in quantum theory. As required by the interpretation of Copenhaghe on the foundations of quantum mechanics, a physical observable is not…

Combinatorics · Mathematics 2015-04-21 Alberto Solís-Encina , José Ramón Portillo

Variable selection for models including interactions between explanatory variables often needs to obey certain hierarchical constraints. The weak or strong structural hierarchy requires that the existence of an interaction term implies at…

Statistics Theory · Mathematics 2016-11-10 Yiyuan She , Zhifeng Wang , He Jiang

We introduce systematic methods to create optimal designs for order-of-addition (OofA) experiments, those that study the order in which $m$ components are applied---for example, the order in which chemicals are added to a reaction or layers…

Methodology · Statistics 2017-11-08 Joseph G. Voelkel

A computer model can be used for predicting an output only after specifying the values of some unknown physical constants known as calibration parameters. The unknown calibration parameters can be estimated from real data by conducting…

Methodology · Statistics 2021-06-18 Arvind Krishna , V. Roshan Joseph , Shan Ba , William A. Brenneman , William R. Myers

For paired comparison experiments involving competing options described by two-level attributes several different methods of constructing designs having block paired observations under the main effects model are presented. These designs are…

Methodology · Statistics 2019-10-16 Eric Nyarko

Existing feature selection methods fail to properly account for interactions between features when evaluating feature subsets. In this paper, we attempt to remedy this issue by using orthogonal variance decomposition to evaluate features.…

Machine Learning · Computer Science 2019-10-23 Firuz Kamalov

We contemplate an experimental situation in a $2^k$-factorial experiment with acute resource crunch so that we need to conduct just a saturated design [SD] - with the understanding that precision of the estimates cannot be estimated from…

Statistics Theory · Mathematics 2019-11-01 Francois Domagni , Samad Hedayat , Sinha Bikas

Nonregular fractional factorial designs such as Plackett-Burman designs and other orthogonal arrays are widely used in various screening experiments for their run size economy and flexibility. The traditional analysis focuses on main…

Methodology · Statistics 2008-12-17 Hongquan Xu , Frederick K. H. Phoa , Weng Kee Wong

This chapter discusses a general design approach to planning computer experiments, which seeks design points that fill a bounded design region as uniformly as possible. Such designs are broadly referred to as space-filling designs.

Methodology · Statistics 2022-03-15 C. Devon Lin , Boxin Tang

Modern software systems often consist of many different components, each with a number of options. Although unit tests may reveal faulty options for individual components, functionally correct components may interact in unforeseen ways to…

Data Structures and Algorithms · Computer Science 2016-06-23 Kaushik Sarkar , Charles J. Colbourn

Overlapping clusters are common in models of many practical data-segmentation applications. Suppose we are given $n$ elements to be clustered into $k$ possibly overlapping clusters, and an oracle that can interactively answer queries of the…

Machine Learning · Computer Science 2019-10-29 Wasim Huleihel , Arya Mazumdar , Muriel Médard , Soumyabrata Pal

This article aims to study efficient/trace optimal designs for crossover trials with multiple responses recorded from each subject in the time periods. A multivariate fixed effects model is proposed with direct and carryover effects…

Methodology · Statistics 2024-06-04 Shubham Niphadkar , Siuli Mukhopadhyay

The increasing size of neural networks has led to a growing demand for methods of efficient fine-tuning. Recently, an orthogonal fine-tuning paradigm was introduced that uses orthogonal matrices for adapting the weights of a pretrained…

Machine Learning · Computer Science 2024-06-17 Mikhail Gorbunov , Nikolay Yudin , Vera Soboleva , Aibek Alanov , Alexey Naumov , Maxim Rakhuba