English
Related papers

Related papers: Average Size of Implicational Bases

200 papers

We study the convergence rates of empirical Bayes posterior distributions for nonparametric and high-dimensional inference. We show that as long as the hyperparameter set is discrete, the empirical Bayes posterior distribution induced by…

Statistics Theory · Mathematics 2020-09-10 Fengshuo Zhang , Chao Gao

This letter gives approximations to an integral appearing in the formula for downlink coverage probability of a typical user in Poisson point process (PPP) based stochastic geometry frameworks of the form $\int_0^\infty \exp\{ - (Ax + B…

Information Theory · Computer Science 2015-10-13 Sudarshan Guruacharya , Hina Tabassum , Ekram Hossain

How should social scientists understand and communicate the uncertainty of statistically estimated causal effects? I propose we utilize the posterior distribution of a causal effect and present the probability of the effect being greater…

Applications · Statistics 2022-11-15 Akisato Suzuki

Recent work of Pickett has given a construction of self-dual normal bases for extensions of finite fields, whenever they exist. In this article we present these results in an explicit and constructive manner and apply them, through computer…

Number Theory · Mathematics 2012-03-06 François Arnault , Erik Jarl Pickett , Stéphane Vinatier

In spite of recent contributions to the literature, informative cluster size settings are not well known and understood. In this paper, we give a formal definition of the problem and describe it from different viewpoints. Data generating…

Statistics Theory · Mathematics 2018-03-06 Jaakko Nevalainen , Somnath Datta , Hannu Oja

The dimension of random simplicial complexes (defined as the maximal dimension among all faces) is a natural extreme value associated with the complex, and is closely related to other functionals defined by a maximum, such as the clique…

Probability · Mathematics 2025-12-19 Kinga Nagy

We develop a constructive piecewise polynomial approximation theory in weighted Sobolev spaces with Muckenhoupt weights for any polynomial degree. The main ingredients to derive optimal error estimates for an averaged Taylor polynomial are…

Numerical Analysis · Mathematics 2014-11-27 Ricardo H. Nochetto , Enrique Otarola , Abner J. Salgado

For any polynomial ideal $I$, let the minimal triangular set contained in the reduced Buchberger-Gr\"obner basis of $I$ with respect to the purely lexicographical term order be called the W-characteristic set of $I$. In this paper, we…

Commutative Algebra · Mathematics 2015-07-01 Dongming Wang

With reference to a baseline parametrization, we explore highly efficient fractional factorial designs for inference on the main effects and, perhaps, some interactions. Our tools include approximate theory together with certain carefully…

Statistics Theory · Mathematics 2014-05-14 Rahul Mukerjee , S. Huda

We introduce intrinsic interpolatory bases for data structured on graphs and derive properties of those bases. Polyharmonic Lagrange functions are shown to satisfy exponential decay away from their centers. The decay depends on the density…

Numerical Analysis · Mathematics 2020-04-21 John Paul Ward , Francis J. Narcowich , Joseph D. Ward

Governments sometimes need to analyse sets of research papers within a field in order to monitor progress, assess the effect of recent policy changes, or identify areas of excellence. They may compare the average citation impacts of the…

Digital Libraries · Computer Science 2015-09-22 Ruth Fairclough , Mike Thelwall

We show that if we have an orthogonal base ($u_1,\ldots,u_p$) in a $p$-dimensional vector space, and select $p+1$ vectors $v_1,\ldots, v_p$ and $w$ such that the vectors traverse the origin, then the probability of $w$ being to closer to…

Probability · Mathematics 2014-04-22 Daniel A. Diaz-Pachon , J. Sunil Rao , Jean-Eudes Dazard

We compute averages of products and ratios of characteristic polynomials associated with Orthogonal, Unitary, and Symplectic Ensembles of Random Matrix Theory. The pfaffian/determinantal formulas for these averages are obtained, and the…

Mathematical Physics · Physics 2007-05-23 A. Borodin , E. Strahov

We observe that the computation $5^2 = 25$ has the digital property of the result being equal to the exponent concatenated directly to the left of the base. The generalization to a Diophantine equation and inequality in number bases has…

History and Overview · Mathematics 2025-12-09 Samer Seraj

We consider coherent sublinear expectations on a measurable space, without assuming the existence of a dominating probability measure. By considering a decomposition of the space in terms of the supports of the measures representing our…

Probability · Mathematics 2011-10-27 Samuel N. Cohen

Random-effects meta-analyses are widely used for evidence synthesis in medical research. However, conventional methods based on large-sample approximations often exhibit poor performance in case of very few studies (e.g., 2 to 4), which is…

Methodology · Statistics 2025-11-20 Ao Huang , Christian Röver , Tim Friede

Uniform convergence of empirical norms - empirical measures of squared functions - is a topic which has received considerable attention in the literature on empirical processes. The results are relevant as empirical norms occur due to…

Statistics Theory · Mathematics 2013-10-22 Sara van de Geer

In this article, we study binomial ideals generated by an arbitrary collection of corner-interval $2$-minors of a generic matrix. We determine the minimal prime ideals of such ideals and characterize their radicality in the special case of…

Commutative Algebra · Mathematics 2025-06-12 Marie Amalore Nambi

We give a description of the minimal primes of the ideal generated by the 2 x 2 adjacent minors of a generic matrix. We also compute the complete prime decomposition of the ideal of adjacent m x m minors of an m x n generic matrix when the…

Commutative Algebra · Mathematics 2007-05-23 Serkan Hosten , Seth Sullivant

The promise of lifted probabilistic inference is to carry out probabilistic inference in a relational probabilistic model without needing to reason about each individual separately (grounding out the representation) by treating the…

Artificial Intelligence · Computer Science 2011-07-22 David Poole , Fahiem Bacchus , Jacek Kisynski