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Approximation techniques have been historically important for solving differential equations, both as initial value problems and boundary value problems. The integration of numerical, analytic and perturbation methods and techniques can…

Classical Analysis and ODEs · Mathematics 2025-02-25 J. Nathan Kutz

Data discretization, also known as binning, is a frequently used technique in computer science, statistics, and their applications to biological data analysis. We present a new method for the discretization of real-valued data into a finite…

Other Quantitative Biology · Quantitative Biology 2007-05-23 Elena S. Dimitrova , John J. McGee , Reinhard C. Laubenbacher

We study the characteristic function and moments of the integer-valued random variable $\lfloor X+\alpha\rfloor$, where $X$ is a continuous random variables. The results can be regarded as exact versions of Sheppard's correction. Rounded…

Probability · Mathematics 2007-05-23 Svante Janson

Compositional data consists of vectors of proportions whose components sum to 1. Such vectors lie in the standard simplex, which is a manifold with boundary. One issue that has been rather controversial within the field of compositional…

Statistics Theory · Mathematics 2019-02-22 Yannis Pantazis , Michail Tsagris , Andrew T. A. Wood

We consider the Cauchy problem for plate equations with rotational inertia and frictional damping terms. We will derive asymptotic profiles of the solution in L^2-sense as time goes to infinity in the case when the initial data have high…

Analysis of PDEs · Mathematics 2019-05-13 Tomonori Fukushima , Ryo Ikehata , Hironori Michihisa

Epistemic uncertainty quantification is a crucial part of drawing credible conclusions from predictive models, whether concerned about the prediction at a given point or any downstream evaluation that uses the model as input. When the…

Machine Learning · Statistics 2022-11-15 Nathan Kallus , James McInerney

We study the relationship between asymptotic characteristic initial data at past null infinity and the regularity of solutions at future null infinity for the massless linear spin-s field equations on Minkowski space. By quantitatively…

General Relativity and Quantum Cosmology · Physics 2023-09-08 Grigalius Taujanskas , Juan A. Valiente Kroon

Causal effect estimation seeks to determine the impact of an intervention from observational data. However, the existing causal inference literature primarily addresses treatment effects on frequently occurring events. But what if we are…

Machine Learning · Statistics 2025-06-18 Jiyuan Tan , Jose Blanchet , Vasilis Syrgkanis

We discuss various methods to obtain the resolution volume for neutron scattering experiments, in order to perform absolute normalization on inelastic magnetic neutron scattering data. Examples from previous experiments are given. We also…

Superconductivity · Physics 2014-02-06 Guangyong Xu , Zhijun Xu , J. M. Tranquada

The results on polarized parton densities (PDFs) obtained using different methods of QCD analysis of the present polarized DIS data are discussed. Their dependence on the method used in the analysis, accounting or not for the kinematic and…

High Energy Physics - Phenomenology · Physics 2009-11-05 Elliot Leader , Aleksander V. Sidorov , Dimiter B. Stamenov

The ultimate purpose of the statistical analysis of ordinal patterns is to characterize the distribution of the features they induce. In particular, knowing the joint distribution of the pair Entropy-Statistical Complexity for a large class…

In this paper, we study the quantization errors of modulo sigma-delta modulated finite, asymptotically-infinite, infinite causal stable ARMA processes. We prove that the normalized quantization error can be taken as a uniformly distributed…

Information Theory · Computer Science 2016-11-17 Li Li , Yudong Chen

Let $\theta_0,\theta_1 \in \mathbb{R}^d$ be the population risk minimizers associated to some loss $\ell:\mathbb{R}^d\times \mathcal{Z}\to\mathbb{R}$ and two distributions $\mathbb{P}_0,\mathbb{P}_1$ on $\mathcal{Z}$. The models…

Statistics Theory · Mathematics 2021-07-13 Dmitrii M. Ostrovskii , Mohamed Ndaoud , Adel Javanmard , Meisam Razaviyayn

We propose a new family of regularized R\'enyi divergences parametrized not only by the order $\alpha$ but also by a variational function space. These new objects are defined by taking the infimal convolution of the standard R\'enyi…

Machine Learning · Statistics 2023-02-16 Jeremiah Birrell , Yannis Pantazis , Paul Dupuis , Markos A. Katsoulakis , Luc Rey-Bellet

Randomization tests are based on a re-randomization of existing data to gain data-dependent critical values that lead to exact hypothesis tests under special circumstances. However, it is not always possible to re-randomize data in…

Statistics Theory · Mathematics 2021-10-20 Dennis Dobler

This dissertation investigates relative entropies, also called generalized divergences, and how they can be used to characterize information-theoretic tasks in quantum information theory. The main goal is to further refine characterizations…

Quantum Physics · Physics 2016-11-29 Felix Leditzky

A formalism for spin observables of the reaction $pd\to ~^3He\eta$ is derived in a model independent way. The general case with a full set of six independent spin amplitudes is studied. Furthermore, approximations by five and four spin…

Nuclear Theory · Physics 2008-11-26 Yu. N. Uzikov

Simultaneous occurrences of extreme events need not imply symmetric or reciprocal tail dependence. However, most existing measures of extremal dependence are inherently symmetric and hence often fail to capture directional influence in tail…

Methodology · Statistics 2026-03-17 Bikramjit Das , Xiangyu Liu

Let \{X_1, X_2, ...\} be a sequence of independent and identically distributed positive random variables of Pareto-type with index \alpha>0 and let \{N(t); t\geq 0\} be a counting process independent of the X_i's. For any fixed t\geq 0,…

Probability · Mathematics 2007-06-13 S. A. Ladoucette , J. L. Teugels

The method of optimizing entropy is used to (i) conduct Asymptotic Hypothesis Testing and (ii) determine the particle distribution for which Entropy is maximized. This paper focuses on two related applications of Information Theory:…

Statistics Theory · Mathematics 2016-03-09 Khizar Qureshi
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