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In this article a special class of nonlinear optimal control problems involving a bilinear term in the boundary condition is studied. These kind of problems arise for instance in the identification of an unknown space-dependent Robin…

Numerical Analysis · Mathematics 2024-12-20 Max Winkler

In the common linear regression model the problem of determining optimal designs for least squares estimation is considered in the case where the observations are correlated. A necessary condition for the optimality of a given design is…

Statistics Theory · Mathematics 2013-03-13 Holger Dette , Andrey Pepelyshev , Anatoly Zhigljavsky

We consider the problem of evaluating designs for a two-arm randomized experiment with an incidence (binary) outcome under a nonparametric general response model. Our two main results are that the priori pair matching design of Greevy et…

Methodology · Statistics 2022-09-02 Adam Kapelner , Abba M. Krieger , David Azriel

In this paper some new properties and computational tools for finding KL-optimum designs are provided. KL-optimality is a general criterion useful to select the best experimental conditions to discriminate between statistical models. A…

Methodology · Statistics 2018-01-04 Giacomo Aletti , Caterina May , Chiara Tommasi

We study the optimal design problems where the goal is to choose a set of linear measurements to obtain the most accurate estimate of an unknown vector in $d$ dimensions. We study the $A$-optimal design variant where the objective is to…

Data Structures and Algorithms · Computer Science 2018-07-18 Aleksandar Nikolov , Mohit Singh , Uthaipon Tao Tantipongpipat

Many existing methods for constructing optimal split-plot designs, such as D-optimal designs, only focus on minimizing the variances and covariances of the estimation for the fitted model. However, the underlying true model is usually…

Computation · Statistics 2016-08-02 Chang-Yun Lin

We consider the optimal design problem for a comparison of two regression curves, which is used to establish the similarity between the dose response relationships of two groups. An optimal pair of designs minimizes the width of the…

Methodology · Statistics 2014-11-19 Holger Dette , Kirsten Schorning

Under a generalised estimating equation analysis approach, approximate design theory is used to determine Bayesian D-optimal designs. For two examples, considering simple exchangeable and exponential decay correlation structures, we compare…

Methodology · Statistics 2024-02-16 Laura Etfer , James M. S. Wason , Michael J. Grayling

We examine the problem of optimal design in the context of filtering multiple random walks. Specifically, we define the steady state E-optimal design criterion and show that the underlying optimization problem leads to a second order cone…

Applications · Statistics 2010-10-07 Harsh Singhal , George Michailidis

We present some optimal criteria to evaluate model-robustness of non-regular two-level fractional factorial designs. Our method is based on minimizing the sum of squares of all the off-diagonal elements in the information matrix, and…

Methodology · Statistics 2009-11-24 Satoshi Aoki

We design optimal $2 \times N$ ($2 <N$) matrices, with unit columns, so that the maximum condition number of all the submatrices comprising 3 columns is minimized. The problem has two applications. When estimating a 2-dimensional signal by…

Information Theory · Computer Science 2012-12-17 Hema Kumari Achanta , Weiyu Xu , Soura Dasgupta

Optimal mechanism design enjoys a beautiful and well-developed theory, and also a number of killer applications. Rules of thumb produced by the field influence everything from how governments sell wireless spectrum licenses to how the major…

Theoretical Economics · Economics 2020-08-12 Tim Roughgarden , Inbal Talgam-Cohen

This paper presents a new and efficient method for the construction of optimal designs for regression models with dependent error processes. In contrast to most of the work in this field, which starts with a model for a finite number of…

Methodology · Statistics 2015-11-06 Holger Dette , Maria Konstantinou , Anatoly Zhigljavsky

We consider the problem of optimally insulating a given domain $\Omega$ of ${\mathbb{R}}^d$; this amounts to solve a nonlinear variational problem, where the optimal thickness of the insulator is obtained as the boundary trace of the…

Optimization and Control · Mathematics 2016-01-12 Dorin Bucur , Giuseppe Buttazzo , Carlo Nitsch

In this paper, we propose two simple yet efficient computational algorithms to obtain approximate optimal designs for multi-dimensional linear regression on a large variety of design spaces. We focus on the two commonly used optimal…

Statistics Theory · Mathematics 2021-02-26 Jiangtao Duan , Wei Gao , Yanyuan Ma , Hon Keung Tony Ng

Systems with both quantitative and qualitative responses are widely encountered in many applications. Design of experiment methods are needed when experiments are conducted to study such systems. Classic experimental design methods are…

Methodology · Statistics 2023-04-24 Lulu Kang , Xinwei Deng , Ran Jin

In this paper, using an optimal partition approach, we study the parametric analysis of a second-order conic optimization problem, where the objective function is perturbed along a fixed direction. We characterize the notions of so-called…

Optimization and Control · Mathematics 2021-06-11 Ali Mohammad-Nezhad , Tamas Terlaky

We consider the problem of obtaining D-optimal designs for factorial experiments with a binary response and $k$ qualitative factors each at two levels. We obtain a characterization for a design to be locally D-optimal. Based on this…

Statistics Theory · Mathematics 2015-03-19 Jie Yang , Abhyuday Mandal , Dibyen Majumdar

We study the problem of optimal subset selection from a set of correlated random variables. In particular, we consider the associated combinatorial optimization problem of maximizing the determinant of a symmetric positive definite matrix…

Computation · Statistics 2019-07-12 Yu Wang , Nhu D. Le , James V. Zidek

Many chemical and biological experiments involve multiple treatment factors and often it is convenient to fit a nonlinear model in these factors. This nonlinear model can be mechanistic, empirical or a hybrid of the two. Motivated by…

Computation · Statistics 2018-10-09 Yuanzhi Huang , Steven Gilmour , Kalliopi Mylona , Peter Goos