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This paper focuses on the numerical approximation of random lattice reversible Selkov systems. It establishes the existence of numerical invariant measures for random models with nonlinear noise, using the backward Euler-Maruyama (BEM)…

Numerical Analysis · Mathematics 2025-10-29 Fang Su , Xue Wang , Xia Pa

We present results from a Monte Carlo simulation of the Nambu - Jona-Lasinio model, with continuous SU(2)xSU(2) chiral symmetry, in four Euclidean dimensions. Different model equations of state, corresponding to different theoretical…

High Energy Physics - Lattice · Physics 2009-10-30 Simon Hands , John B. Kogut

Methods for Bayesian simulation in the presence of computationally intractable likelihood functions are of growing interest. Termed likelihood-free samplers, standard simulation algorithms such as Markov chain Monte Carlo have been adapted…

Computation · Statistics 2010-05-31 S. A. Sisson , G. W. Peters , M. Briers , Y. Fan

Accurate uncertainty quantification (UQ) in Large Language Models (LLMs) is critical for trustworthy deployment. While real-world language is inherently ambiguous, reflecting aleatoric uncertainty, existing UQ methods are typically…

Machine Learning · Computer Science 2026-01-30 Tim Tomov , Dominik Fuchsgruber , Tom Wollschläger , Stephan Günnemann

For a regression model, we consider the risk of the maximum likelihood estimator with respect to $\alpha$-divergence, which includes the special cases of Kullback-Leibler divergence, Hellinger distance and $\chi^2$ divergence. The…

Statistics Theory · Mathematics 2017-09-12 Yo Sheena

In threshold-based anomaly detection, we want to tune the threshold of a detector to achieve an acceptable false alarm rate. However, tuning the threshold is often a non-trivial task due to unknown detector output distributions. A detector…

Systems and Control · Electrical Eng. & Systems 2022-05-02 David Umsonst , Justin Ruths , Henrik Sandberg

Accelerated life-testing (ALT) is a very useful technique for examining the reliability of highly reliable products. It allows testing the products at higher than usual stress conditions to induce failures more quickly and economically than…

Statistics Theory · Mathematics 2020-05-15 Aida Calviño

Diffusion processes with small noise conditioned to reach a target set are considered. The AMS algorithm is a Monte Carlo method that is used to sample such rare events by iteratively simulating clones of the process and selecting…

Numerical Analysis · Mathematics 2022-12-12 Frédéric Cérou , Sofiane Martel , Mathias Rousset

Consider a central problem in randomized approximation schemes that use a Monte Carlo approach. Given a sequence of independent, identically distributed random variables $X_1,X_2,\ldots$ with mean $\mu$ and standard deviation at most $c…

Statistics Theory · Mathematics 2014-11-18 Mark Huber

A novel test in the linear $\ell_1$ (LAD) and quantile regressions is proposed, based on the scores provided by the dual variables (signs) arising in the calculation of the (so-called) affine-lasso estimate--a Rao-type, Lagrange multiplier…

Methodology · Statistics 2025-12-23 Sylvain Sardy , Ivan Mizera , Xiaoyu Ma , Hugo Gaible

Covariance Structure Analysis (CSA) or Structural Equation Modeling (SEM) is critical for political scientists measuring latent structural relationships, allowing for the simultaneous assessment of both latent and observed variables,…

Methodology · Statistics 2024-11-20 Bang Quan Zheng , Peter M. Bentler

We consider goodness-of-fit tests for uniformity of a multinomial distribution by means of tests based on a class of symmetric statistics, defined as the sum of some function of cell-frequencies. We are dealing with an asymptotic regime,…

Statistics Theory · Mathematics 2022-11-03 Sherzod M Mirakhmedov

Exactification is the process of obtaining exact values of a function from its complete asymptotic expansion. Here Stirling's approximation for the logarithm of the gamma function or $\ln \Gamma(z)$ is derived completely whereby it is…

Classical Analysis and ODEs · Mathematics 2021-02-16 Victor Kowalenko

A recent article on generalised linear mixed model asymptotics, Jiang et al. (2022), derived the rates of convergence for the asymptotic variances of maximum likelihood estimators. If $m$ denotes the number of groups and $n$ is the average…

Statistics Theory · Mathematics 2023-04-03 Luca Maestrini , Aishwarya Bhaskaran , Matt P. Wand

Signal amplitude estimation and detection from unlabeled quantized binary samples are studied, assuming that the order of the time indexes is completely unknown. First, maximum likelihood (ML) estimators are utilized to estimate both the…

Information Theory · Computer Science 2018-08-15 Guanyu Wang , Jiang Zhu , Rick S. Blum , Peter Willett , Stefano Marano , Vincenzo Matta , Paolo Braca

Quantum mechanics for many-body systems may be reduced to the evaluation of integrals in 3N dimensions using Monte-Carlo, providing the Quantum Monte Carlo ab initio methods. Here we limit ourselves to expectation values for trial…

Computational Physics · Physics 2010-11-22 John Robert Trail , Ryo Maezono

This paper investigates the asymptotic distribution of the maximum-likelihood estimate (MLE) in multinomial logistic models in the high-dimensional regime where dimension and sample size are of the same order. While classical large-sample…

Statistics Theory · Mathematics 2023-05-30 Kai Tan , Pierre C. Bellec

We propose a simple test for moment inequalities that has exact size in normal models with known variance and has uniformly asymptotically exact size more generally. The test compares the quasi-likelihood ratio statistic to a chi-squared…

Econometrics · Economics 2020-08-19 Gregory Cox , Xiaoxia Shi

Testing independence is of significant interest in many important areas of large-scale inference. Using extreme-value form statistics to test against sparse alternatives and using quadratic form statistics to test against dense alternatives…

Statistics Theory · Mathematics 2015-12-31 Danning Li , Lingzhou Xue

This article considers the sequential Monte Carlo (SMC) approximation of ratios of normalizing constants associated to posterior distributions which in principle rely on continuum models. Therefore, the Monte Carlo estimation error and the…

Computation · Statistics 2016-03-04 Pierre Del Moral , Ajay Jasra , Kody Law , Yan Zhou