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We consider nonregular fractions of factorial experiments for a class of linear models. These models have a common general mean and main effects, however they may have different 2-factor interactions. Here we assume for simplicity that…

Computation · Statistics 2019-11-11 Shrabanti Chowdhury , Joshua Lukemire , Abhyuday Mandal

Given any polynomial system with fixed monomial term structure, we give explicit formulae for the generic number of roots with specified coordinate vanishing restrictions. For the case of affine space minus an arbitrary union of coordinate…

Algebraic Geometry · Mathematics 2016-09-06 J. Maurice Rojas

This paper considers the construction of minimum aberration (MA) blocked factorial designs. Based on coding theory, the concept of minimum moment aberration due to Xu [Statist. Sinica 13 (2003) 691--708] for unblocked designs is extended to…

Statistics Theory · Mathematics 2007-06-13 Hongquan Xu

Spaces with locally varying scale of measurement, like multidimensional structures with differently scaled dimensions, are pretty common in statistics and machine learning. Nevertheless, it is still understood as an open question how to…

Machine Learning · Statistics 2024-03-05 Christoph Jansen , Georg Schollmeyer , Hannah Blocher , Julian Rodemann , Thomas Augustin

The vertices of a finite state system are usually a subset of the natural numbers. Most algorithms relative to these systems only use this fact to select vertices. For infinite state systems, however, the situation is different: in…

Formal Languages and Automata Theory · Computer Science 2009-11-18 Christophe Morvan

New types of designs called nested space-filling designs have been proposed for conducting multiple computer experiments with different levels of accuracy. In this article, we develop several approaches to constructing such designs. The…

Statistics Theory · Mathematics 2009-09-04 Peter Z. G. Qian , Mingyao Ai , C. F. Jeff Wu

A new construction of naturally reductive spaces is presented. This construction gives a large amount of new families of naturally reductive spaces. First the infinitesimal models of the new naturally reductive spaces are constructed. A…

Differential Geometry · Mathematics 2016-05-03 Reinier Storm

Space-filling designs are important in computer experiments, which are critical for building a cheap surrogate model that adequately approximates an expensive computer code. Many design construction techniques in the existing literature are…

Methodology · Statistics 2022-08-30 Chaofan Huang , V. Roshan Joseph , Douglas M. Ray

We introduce symmetric arithmetic circuits, i.e. arithmetic circuits with a natural symmetry restriction. In the context of circuits computing polynomials defined on a matrix of variables, such as the determinant or the permanent, the…

Computational Complexity · Computer Science 2024-01-22 Anuj Dawar , Gregory Wilsenach

Randomization procedures are used in legal and statistical applications, aiming to shield important decisions from spurious influences. This article gives an intuitive introduction to randomization and examines some intended consequences of…

We propose a new family of combinatorial inference problems for graphical models. Unlike classical statistical inference where the main interest is point estimation or parameter testing, combinatorial inference aims at testing the global…

Statistics Theory · Mathematics 2018-02-14 Matey Neykov , Junwei Lu , Han Liu

We introduce a notion of compatibility between constraint encoding and compositional structure. Phrased in the language of category theory, it is given by a "composable constraint encoding". We show that every composable constraint encoding…

Category Theory · Mathematics 2021-12-14 Matt Wilson , Augustin Vanrietvelde

An {\em $m\times n$ row-column factorial design} is an arrangement of the elements of a factorial design into a rectangular array. Such an array is used in experimental design, where the rows and columns can act as blocking factors. If for…

Statistics Theory · Mathematics 2021-01-18 Fahim Rahim , Nicholas Cavenagh

One aspect of evaluating the design for an experiment is the discovery of the relationships between subspaces of the data space. Initially we establish the notation and methods for evaluating an experiment with a single randomization.…

Statistics Theory · Mathematics 2009-11-23 C. J. Brien , R. A. Bailey

We investigate different randomizations for mirror descent method. We try to propose such a randomization that allows us to use sparsity of the problem as much as it possible. In the paper one can also find a generalization of randomizaed…

Optimization and Control · Mathematics 2016-12-12 Anton Anikin , Alexander Gasnikov , Alexander Gornov

The family of visibility algorithms were recently introduced as mappings between time series and graphs. Here we extend this method to characterize spatially extended data structures by mapping scalar fields of arbitrary dimension into…

Data Analysis, Statistics and Probability · Physics 2017-09-13 Lucas Lacasa , Jacopo Iacovacci

The graphical notion of effective resistance has found wide-ranging applications in many areas of pure mathematics, applied mathematics and control theory. By the nature of its construction, effective resistance can only be computed in…

Optimization and Control · Mathematics 2013-10-23 George Forrest Young , Luca Scardovi , Naomi Ehrich Leonard

Experimental design has emerged as a powerful approach for improving the sample efficiency of A/B testing, yet existing designs rely critically on correctly specified models. We study robust sequential experimental design under model…

Machine Learning · Statistics 2026-05-14 Qianglin Wen , Xiangkun Wu , Chengchun Shi , Ting Li , Niansheng Tang , Yingying Zhang , Hongtu Zhu

We investigate numerically efficient approximations of eigenspaces associated to symmetric and general matrices. The eigenspaces are factored into a fixed number of fundamental components that can be efficiently manipulated (we consider…

Machine Learning · Computer Science 2021-09-29 Cristian Rusu , Lorenzo Rosasco

Spatial confounding is how is called the confounding between fixed and spatial random effects. It has been widely studied and it gained attention in the past years in the spatial statistics literature, as it may generate unexpected results…