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Related papers: Design and analysis for constrained order-of-addit…

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In the chemical, pharmaceutical, and food industries, sometimes the order of adding a set of components has an impact on the final product. These are instances of the order-of-addition (OofA) problem, which aims to find the optimal sequence…

Methodology · Statistics 2024-11-07 Jiayi Zheng , Nicholas Rios

In a mixture experiment, we study the behavior and properties of $m$ mixture components, where the primary focus is on the proportions of the components that make up the mixture rather than the total amount. Mixture-amount experiments are…

Methodology · Statistics 2025-10-29 Taha Hasan , Touqeer Ahmad

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

In an order-of-addition experiment, each treatment is a permutation of m components. It is often unaffordable to test all the m! treatments, and the design problem arises. We consider a model that incorporates the order of each pair of…

Statistics Theory · Mathematics 2018-05-15 Jiayu Peng , Rahul Mukerjee , Dennis K. J. Lin

Designs for Order-of-Addition (OofA) experiments have received growing attention due to their impact on responses based on the sequence of component addition. In certain cases, these experiments involve heterogeneous groups of units, which…

Methodology · Statistics 2026-02-04 Chang-Yun Lin

The purpose of order-of-addition (OofA) experiments is to identify the best order in a sequence of m components in a system or treatment. Such experiments may be analysed by various regression models, the most popular ones being based on…

Methodology · Statistics 2021-01-27 Hans-Peter Piepho , Emlyn R. Williams

Mixture experiments often involve process variables, such as different chemical reactors in a laboratory or varying mixing speeds in a production line. Organizing the runs in orthogonal blocks allows the mixture model to be fitted…

Methodology · Statistics 2024-10-31 Taha Hasan , Touqeer Ahmad

In computer experiments, it has become a standard practice to select the inputs that spread out as uniformly as possible over the design space. The resulting designs are called space-filling designs and they are undoubtedly desirable…

Methodology · Statistics 2025-05-06 Guangzhou Chen , Yuanzhen He , C. Devon Lin , Fasheng Sun

Traditional methods for covariate adjustment of treatment means in designed experiments are inherently conditional on the observed covariate values. In order to develop a coherent general methodology for analysis of covariance, we propose a…

Methodology · Statistics 2010-01-19 James G. Booth , Walter T. Federer , Martin T. Wells , Russell D. Wolfinger

Order-of-addition experiments arise when the response depends on the order in which a set of components is added. Since the number of possible orders increases factorially with the number of components, full permutation designs are rarely…

Methodology · Statistics 2026-05-27 Hui Shao , Yaping Wang , Qian Xiao

We present a new experimental design procedure that divides a set of experimental units into two groups in order to minimize error in estimating an additive treatment effect. One concern is minimizing error at the experimental design stage…

Methodology · Statistics 2021-02-02 Abba M. Krieger , David Azriel , Adam Kapelner

This paper considers the design of observational longitudinal studies with a continuous response and a binary time-invariant exposure, where, typically, the exposure is unbalanced, the mean response in the two groups differs at baseline and…

Methodology · Statistics 2022-09-27 Xavier Basagana , Donna Spiegelman

Matching mechanisms play a central role in operations management across diverse fields including education, healthcare, and online platforms. However, experimentally comparing a new matching algorithm against a status quo presents some…

Methodology · Statistics 2026-01-30 Chonghuan Wang

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

The design of experiments in psychology can often be summarized to participants reacting to stimuli. For such an experiment, the mixed effects model with crossed random effects is usually the appropriate tool to analyse the data because it…

Methodology · Statistics 2020-10-19 Jaromil Frossard , Olivier Renaud

The performance of multiobjective algorithms varies across problems, making it hard to develop new algorithms or apply existing ones to new problems. To simplify the development and application of new multiobjective algorithms, there has…

Neural and Evolutionary Computing · Computer Science 2022-07-08 Yuri Lavinas , Marcelo Ladeira , Gabriela Ochoa , Claus Aranha

The study of combinations of drugs/drug-schedules gained increasing attention in various therapeutic areas recently. In oncology, the aim of phase I combination clinical trial is to find the maximum tolerated combination (MTC). Many…

Methodology · Statistics 2025-05-09 Weishi Chen , Pavel Mozgunov

Bayesian optimal experimental design (OED) seeks to conduct the most informative experiment under budget constraints to update the prior knowledge of a system to its posterior from the experimental data in a Bayesian framework. Such…

Machine Learning · Computer Science 2024-02-29 Rafael Orozco , Felix J. Herrmann , Peng Chen

Coupled phase-oscillators are important models related to synchronization. Recently, Ott-Antonsen(OA) ansatz is developed and used to get low-dimensional collective behaviors in coupled oscillator systems. In this paper, we develop a simple…

Adaptation and Self-Organizing Systems · Physics 2015-09-17 Jian Gao , Can Xu , Yuting Sun , Zhigang Zheng

Integrating the outputs of multiple classifiers via combiners or meta-learners has led to substantial improvements in several difficult pattern recognition problems. In the typical setting investigated till now, each classifier is trained…

Machine Learning · Computer Science 2007-05-23 Kagan Tumer , Joydeep Ghosh
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