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Related papers: Pad\'{e} approximants and exact two-locus sampling…

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For positive integers $d$ and $p$ such that $d \ge p$, let $\mathbb{R}^{d \times p}$ denote the set of $d \times p$ real matrices, $I_p$ be the identity matrix of order $p$, and $V_{d,p} = \{x \in \mathbb{R}^{d \times p} \mid x'x = I_p\}$…

Statistics Theory · Mathematics 2024-10-22 Armine Bagyan , Donald Richards

In this paper, we introduce a notion of expansion for groupoids, which recovers the classical notion of expander graphs by a family of pair groupoids and expanding actions in measure by transformation groupoids. We also consider an…

Operator Algebras · Mathematics 2025-06-23 Xulong Lu , Qin Wang , Jiawen Zhang

In this paper we extend our recent work on two-dimensional (2D) diffusive search-and-capture processes with multiple small targets (narrow capture problems) by considering an asymptotic expansion of the Laplace transformed probability flux…

Statistical Mechanics · Physics 2021-04-28 Paul C Bressloff

Pad\'e approximants are rational functions whose series expansion match a given series as far as possible. These approximants are usually written under a rational form. In this paper, we will show how to write them also under two different…

Numerical Analysis · Mathematics 2014-04-29 Claude Brezinski , Michela Redivo-Zaglia

Given an observable and its operator product expansion (OPE), we present expressions that carefully disentangle truncated sums of the perturbative series in powers of $\alpha$ from the non-perturbative (NP) corrections. This splitting is…

High Energy Physics - Theory · Physics 2019-04-24 Cesar Ayala , Xabier Lobregat , Antonio Pineda

Motivated by real-world machine learning applications, we analyze approximations to the non-asymptotic fundamental limits of statistical classification. In the binary version of this problem, given two training sequences generated according…

Information Theory · Computer Science 2018-12-07 Lin Zhou , Vincent Y. F. Tan , Mehul Motani

New algorithms for construction of asymptotic expansions for stationary distributions of nonlinearly perturbed semi-Markov processes with finite phase spaces are presented. These algorithms are based on a special technique of sequential…

Probability · Mathematics 2016-03-16 Dmitrii Silvestrov , Sergei Silvestrov

With the growing availability of large-scale biomedical data, it is often time-consuming or infeasible to directly perform traditional statistical analysis with relatively limited computing resources at hand. We propose a fast subsampling…

Methodology · Statistics 2023-05-18 Haixiang Zhang , Lulu Zuo , HaiYing Wang , Liuquan Sun

Rejective sampling improves design and estimation efficiency of single-phase sampling when auxiliary information in a finite population is available. When such auxiliary information is unavailable, we propose to use two-phase rejective…

Methodology · Statistics 2025-01-14 Shu Yang , Peng Ding

We propose a novel resampling-based method to construct an asymptotically exact test for any subset of hypotheses on coefficients in high-dimensional linear regression. It can be embedded into any multiple testing procedure to make…

Methodology · Statistics 2022-05-26 Anna Vesely , Jelle J. Goeman , Livio Finos

We consider the sampling of the coupled cluster expansion within stochastic coupled cluster theory. Observing the limitations of previous approaches due to the inherently non-linear behaviour of a coupled cluster wavefunction representation…

Chemical Physics · Physics 2018-08-14 Charles J. C. Scott , Alex J. W. Thom

We establish some asymptotic expansions for infinite weighted convolutions of distributions having light subexponential tails. Examples are presented, some showing that in order to obtain an expansion with two significant terms, one needs…

Probability · Mathematics 2007-06-13 Ph. Barbe , W. P. McCormick

New algorithms for computing of asymptotic expansions for stationary distributions of nonlinearly perturbed semi-Markov processes are presented. The algorithms are based on special techniques of sequential phase space reduction, which can…

Probability · Mathematics 2017-03-08 Dmitrii Silvestrov , Sergei Silvestrov

We present a technique for approximating generic normalization constants subject to constraints. The method is then applied to derive the exact asymptotics for the conditional normalization constant of constrained exponential random graphs.

Probability · Mathematics 2015-08-05 Mei Yin

The critical behavior of two-dimensional $n$-vector $\lambda\phi^4$ field model is studied within the framework of pseudo-$\epsilon$ expansion approach. Pseudo-$\epsilon$ expansions for Wilson fixed point location $g^*$ and critical…

Statistical Mechanics · Physics 2015-06-18 M. A. Nikitina , A. I. Sokolov

The paper presents a novel asymptotic distribution for a mle when the log--likelihood is strictly concave in the parameter for all data points; for example, the exponential family. The new asymptotic distribution can be seen as a refinement…

Statistics Theory · Mathematics 2021-06-15 Stephen G Walker

This paper develops an asymptotic expansion technique in momentum space for stochastic filtering. It is shown that Fourier transformation combined with a polynomial-function approximation of the nonlinear terms gives a closed recursive…

Computational Finance · Quantitative Finance 2013-03-26 Masaaki Fujii

Recently, there has been renewed interest in studying the asymptotic properties of the integer partition function $p(n)$. Hardy, Ramanujan, and Rademacher provided detailed asymptotic analysis for $p(n)$. Presently, attention has shifted…

Number Theory · Mathematics 2024-11-13 Gergő Nemes

SLOPE is a relatively new convex optimization procedure for high-dimensional linear regression via the sorted l1 penalty: the larger the rank of the fitted coefficient, the larger the penalty. This non-separable penalty renders many…

Machine Learning · Statistics 2019-07-18 Zhiqi Bu , Jason Klusowski , Cynthia Rush , Weijie Su

We describe an extension of the Taylor method for the numerical solution of ODEs that uses Pad\'e approximants to obtain extremely precise numerical results. The accuracy of the results is essentially limited only by the computer time and…

Computational Physics · Physics 2022-05-04 Paolo Amore