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Related papers: Uniform fractional factorial designs

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Recent researches on designs for computer experiments with both qualitative and quantitative factors have advocated the use of marginally coupled designs. This paper proposes a general method of constructing such designs for which the…

Methodology · Statistics 2022-03-15 Yuanzhen He , C. Devon Lin , Fasheng SUn

Using the standard finite element method (FEM) to solve general partial differential equations, the round-off error is found to be proportional to $N^{\beta_{\rm R}}$, with $N$ the number of degrees of freedom (DoFs) and $\beta_{\rm R}$ a…

Numerical Analysis · Mathematics 2022-02-08 Jie Liu , Henk M. Schuttelaars , Matthias Möller

Multifactorial experimental designs allow us to assess the contribution of several factors, and potentially their interactions, to one or several responses of interests. Following the principles of the partition of the variance advocated by…

The paper considers the design of minimum phase discrete linear arrays. The paper introduces recent advances for the design of minimum phase Finite Impulse Response filters, as applied to the design of minimum phase linear arrays. The…

Signal Processing · Electrical Eng. & Systems 2022-12-22 Jan C Olivier , Etienne Barnard

We build a simple diagnostic criterion for approximate factor structure in large cross-sectional equity datasets. Given a model for asset returns with observable factors, the criterion checks whether the error terms are weakly…

Statistical Finance · Quantitative Finance 2017-08-08 Patrick Gagliardini , Elisa Ossola , Olivier Scaillet

We extend Robust Optimization to fractional programming, where both the objective and the constraints contain uncertain parameters. Earlier work did not consider uncertainty in both the objective and the constraints, or did not use Robust…

Optimization and Control · Mathematics 2015-08-21 Bram L. Gorissen

Approximation using Fourier features is a popular technique for scaling kernel methods to large-scale problems, with myriad applications in machine learning and statistics. This method replaces the integral representation of a…

Machine Learning · Statistics 2024-08-26 Ayoub Belhadji , Qianyu Julie Zhu , Youssef Marzouk

Distributionally balanced sampling designs are low-discrepancy probability designs obtained by minimizing the expected discrepancy between the auxiliary-variable distribution of a random sample and the target population distribution.…

Methodology · Statistics 2026-03-26 Anton Grafström , Wilmer Prentius

The least square solution of minimum norm of a rectangular linear system of equations can be found out iteratively by using matrix splittings. However, the convergence of such an iteration scheme arising out of a matrix splitting is…

Numerical Analysis · Mathematics 2025-08-07 Chinmay Kumar Giri , Debasisha Mishra

We obtain minimax-optimal convergence rates in the supremum norm, including information-theoretic lower bounds, for estimating the covariance kernel of a stochastic process which is repeatedly observed at discrete, synchronous design…

Statistics Theory · Mathematics 2025-09-03 Max Berger , Hajo Holzmann

Fractional equations have become the model of choice in several applications where heterogeneities at the microstructure result in anomalous diffusive behavior at the macroscale. In this work we introduce a new fractional operator…

Numerical Analysis · Mathematics 2021-01-29 Marta D'Elia , Christian Glusa

Diffusion models are learning pattern-learning systems to model and sample from data distributions with three functional components namely the forward process, the reverse process, and the sampling process. The components of diffusion…

Machine Learning · Computer Science 2025-06-02 Ziyi Chang , George Alex Koulieris , Hyung Jin Chang , Hubert P. H. Shum

In a physical design problem, the designer chooses values of some physical parameters, within limits, to optimize the resulting field. We focus on the specific case in which each physical design parameter is the ratio of two field…

Optimization and Control · Mathematics 2020-02-19 Guillermo Angeris , Jelena Vučković , Stephen Boyd

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

In this paper the fractional order logistic map in the sense of Caputo's fractional differences is numerically approached. It is shown that the necessary iterations number to avoid transients must be of order of thousand, not of order of…

Numerical Analysis · Mathematics 2022-03-08 Marius-F. Danca

There are multiple cluster randomised trial designs that vary in when the clusters cross between control and intervention states, when observations are made within clusters, and how many observations are made at that time point. Identifying…

Methodology · Statistics 2023-07-20 Samuel I. Watson , Alan Girling , Karla Hemming

In this paper optimal experimental designs for inverse quadratic regression models are determined. We consider two different parameterizations of the model and investigate local optimal designs with respect to the $c$-, $D$- and…

Methodology · Statistics 2008-09-30 H. Dette , C. Kiss

In the paper we study the subject of positivity of systems with sequential fractional difference. We give formulas for the unique solutions of systems in linear and semi-linear cases. The positivity of systems is considered.

Dynamical Systems · Mathematics 2013-04-15 Ewa Girejko , Dorota Mozyrska , Małgorzata Wyrwas

The design of efficient quantum circuits is an important issue in quantum computing. It is in general a formidable task to find a highly optimized quantum circuit for a given unitary matrix. We propose a quantum circuit design method that…

Quantum Physics · Physics 2023-11-27 Andreas Klappenecker , Martin Roetteler

Row-column factorial designs that provide unconfounded estimation of all main effects and the maximum number of two-factor interactions (2fi's) are called 2fi-optimal. This issue has been paid great attention recently for its wide…

Statistics Theory · Mathematics 2023-08-02 Yingnan Zhang , Jiangmin Pan , Lei Shi
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