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We deduce the asymptotic error distribution of the Euler method for the nonlinear filtering problem with continuous-time observations. Previous works by several authors have shown that the error structure of the method is characterized by…

Probability · Mathematics 2018-09-10 Teppei Ogihara , Hideyuki Tanaka

We present improved methods for calculating confidence intervals and $p$-values in situations where standard asymptotic approaches fail due to small sample sizes. We apply these techniques to a specific class of statistical model that can…

Data Analysis, Statistics and Probability · Physics 2024-01-11 Enzo Canonero , Alessandra Rosalba Brazzale , Glen Cowan

In this work, we provide a non-asymptotic convergence analysis of projected gradient descent for physics-informed neural networks for the Poisson equation. Under suitable assumptions, we show that the optimization error can be bounded by…

Optimization and Control · Mathematics 2025-05-13 Jonas Nießen , Johannes Müller

We propose two types of universal codes that are suited to two asymptotic regimes when the output alphabet is possibly continuous. The first class has the property that the error probability decays exponentially fast and we identify an…

Information Theory · Computer Science 2024-09-10 Masahito Hayashi

We consider classical $O(N)$ vector models in dimension three and higher and investigate the nature of the low-temperature expansions for their multipoint spin correlations. We prove that such expansions define asymptotic series, and derive…

Mathematical Physics · Physics 2025-03-12 Alessandro Giuliani , Sébastien Ott

The problem of estimating a linear functional based on observational data is canonical in both the causal inference and bandit literatures. We analyze a broad class of two-stage procedures that first estimate the treatment effect function,…

Statistics Theory · Mathematics 2022-09-28 Wenlong Mou , Martin J. Wainwright , Peter L. Bartlett

This article examines the accuracy for large times of asymptotic expansions from periodic homogenization of wave equations. As usual, $\epsilon$ denotes the small period of the coefficients in the wave equation. We first prove that the…

Analysis of PDEs · Mathematics 2018-03-28 Grégoire Allaire , Agnes Lamacz , Jeffrey Rauch

We consider the classical problem of learning, with arbitrary accuracy, the natural parameters of a $k$-parameter truncated \textit{minimal} exponential family from i.i.d. samples in a computationally and statistically efficient manner. We…

Machine Learning · Computer Science 2023-09-13 Abhin Shah , Devavrat Shah , Gregory W. Wornell

Under the Riemann Hypothesis, we improve the error term in the asymptotic formula related to the counting lattice problem studied in a first part of this work. The improvement comes from the use of Weyl's bound for exponential sums of…

Number Theory · Mathematics 2017-09-27 Olivier Bordellès

A new maximum likelihood method for deconvoluting a continuous density with a positive lower bound on a known compact support in additive measurement error models with known error distribution using the approximate Bernstein type polynomial…

Methodology · Statistics 2018-01-30 Zhong Guan

We consider the asymptotic behavior of the multidimensional Laplace-type integral with a perturbed phase function. Under suitable assumptions, we derive a higher-order asymptotic expansion with an error estimate, generalizing some previous…

Classical Analysis and ODEs · Mathematics 2025-12-11 Ikki Fukuda , Yoshiki Kagaya , Yuki Ueda

We demonstrate how the asymptotics for large $|z|$ of the generalised Bessel function \[{}_0\Psi_1(z)=\sum_{n=0}^\infty\frac{z^n}{\Gamma(an+b) n!},\] where $a>-1$ and $b$ is any number (real or complex), may be obtained by exploiting the…

Classical Analysis and ODEs · Mathematics 2020-06-16 R B Paris

We revisit the standard ``telescoping sum'' argument ubiquitous in the final steps of analyzing evaluation complexity of algorithms for smooth nonconvex optimization, and obtain a refined formulation of the resulting bound as a function of…

Optimization and Control · Mathematics 2024-08-20 Serge Gratton , Chee-Khian Sim , Philippe L. Toint

The $k$-means problem is a classic objective for modeling clustering in a metric space. Given a set of points in a metric space, the goal is to find $k$ representative points so as to minimize the sum of the squared distances from each…

Computational Geometry · Computer Science 2026-03-31 Vincent Cohen-Addad , Karthik C. S. , David Saulpic , Chris Schwiegelshohn

We review recent studies of the operator product expansion of the plaquette and of the associated determination of the gluon condensate. One first needs the perturbative expansion to orders high enough to reach the asymptotic regime where…

High Energy Physics - Phenomenology · Physics 2021-09-06 Antonio Pineda

Let $d(n)$ be the number of divisors of $n$, let $\gamma$ denote Euler's constant and $$ \Delta(x) := \sum_{n\le x}d(n) - x(\log x + 2\gamma -1) $$ denote the error term in the classical Dirichlet divisor problem, and let $\zeta(s)$ denote…

Number Theory · Mathematics 2015-12-07 Aleksandar Ivić , Wenguang Zhai

In this paper we present the Edgeworth expansion for the Euler approximation scheme of a continuous diffusion process driven by a Brownian motion. Our methodology is based upon a recent work \cite{Yoshida2013}, which establishes Edgeworth…

Probability · Mathematics 2018-11-20 Mark Podolskij , Bezirgen Veliyev , Nakahiro Yoshida

Asymptotic error distribution for approximation of a stochastic integral with respect to continuous semimartingale by Riemann sum with general stochastic partition is studied. Effective discretization schemes of which asymptotic conditional…

Probability · Mathematics 2010-04-14 Masaaki Fukasawa

We derive asymptotic expansions of the large zeros of the Coulomb wave functions and for those of their derivatives. The new expansions have the same form as the McMahon expansions of the zeros of the Bessel functions and reduce to them…

Classical Analysis and ODEs · Mathematics 2024-08-13 Amparo Gil , Javier Segura , Nico M. Temme

We study the phenomenon of loss of lock in the optimal non-causal phase estimation problem, a benchmark problem in nonlinear estimation. Our method is based on the computation of the asymptotic distribution of the optimal estimation error…

Optimization and Control · Mathematics 2008-02-05 Doron Ezri , Ben-Tzion Bobrovsky , Zeev Schuss