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It is well known that, under standard regularity conditions, the maximum likelihood estimator (MLE) satisfies a central limit theorem and converges in distribution to a Gaussian random variable as the sample size grows. This paper…

Information Theory · Computer Science 2026-05-26 Leighton P. Barnes , Alex Dytso

Prompt sensitivity, which refers to how strongly the output of a large language model (LLM) depends on the exact wording of its input prompt, raises concerns among users about the LLM's stability and reliability. In this work, we consider…

Computation and Language · Computer Science 2026-04-21 Yang Liu , Chenhui Chu

A parametric theory of statistical inference is developed for the moderate deviation probability zone. The new approach to the proofs is based on the Taylor series expansion of the logarithm of the likelihood ratio based on the Hellinger…

Statistics Theory · Mathematics 2026-04-28 Mikhail Ermakov

We consider a finite sequence of random points in a finite domain of a finite-dimensional Euclidean space. The points are sequentially allocated in the domain according to a model of cooperative sequential adsorption. The main peculiarity…

Probability · Mathematics 2009-11-11 V. Shcherbakov

We study random spatial permutations on Z^3 where each jump x -> \pi(x) is penalized by a factor exp(-T ||x-\pi(x)||^2). The system is known to exhibit a phase transition for low enough T where macroscopic cycles appear. We observe that the…

Statistical Mechanics · Physics 2012-03-20 Stefan Grosskinsky , Alexander A. Lovisolo , Daniel Ueltschi

In recent years, the shortcomings of Bayesian posteriors as inferential devices have received increased attention. A popular strategy for fixing them has been to instead target a Gibbs measure based on losses that connect a parameter of…

Statistics Theory · Mathematics 2025-04-24 David T. Frazier , Jeremias Knoblauch , Jack Jewson , Christopher Drovandi

Variable Length Memory Chains (VLMC), which are generalizations of finite order Markov chains, turn out to be an essential tool to modelize random sequences in many domains, as well as an interesting object in contemporary probability…

Probability · Mathematics 2020-04-20 Peggy Cénac , Brigitte Chauvin , Camille Noûs , Frédéric Paccaut , Nicolas Pouyanne

The Conway-Maxwell-Poisson distribution is a two-parameter generalisation of the Poisson distribution that can be used to model data that is under- or over-dispersed relative to the Poisson distribution. The normalizing constant…

Statistics Theory · Mathematics 2019-04-05 Robert E. Gaunt , Satish Iyengar , Adri B. Olde Daalhuis , Burcin Simsek

Asymptotics of the normalizing constant is computed for a class of one parameter exponential families on permutations which includes Mallows model with Spearmans's Footrule and Spearman's Rank Correlation Statistic. The MLE, and a…

Probability · Mathematics 2016-05-05 Sumit Mukherjee

This paper is part of the ongoing effort to study high-dimensional permutations. We prove the analogue to the Erd\H{o}s-Szekeres theorem: For every $k\ge1$, every order-$n$ $k$-dimensional permutation contains a monotone subsequence of…

Combinatorics · Mathematics 2017-10-24 Nathan Linial , Michael Simkin

This paper focuses on the size-biased permutation of $n$ independent and identically distributed (i.i.d.) positive random variables. This is a finite dimensional analogue of the size-biased permutation of ranked jumps of a subordinator…

Probability · Mathematics 2015-09-30 Jim Pitman , Ngoc M. Tran

The similarity between a pair of time series, i.e., sequences of indexed values in time order, is often estimated by the dynamic time warping (DTW) distance, instead of any in the well-studied family of measures including the longest common…

Data Structures and Algorithms · Computer Science 2022-04-19 Yoshifumi Sakai , Shunsuke Inenaga

Variational inference has become one of the most widely used methods in latent variable modeling. In its basic form, variational inference employs a fully factorized variational distribution and minimizes its KL divergence to the posterior.…

Machine Learning · Statistics 2020-01-29 Robert Bamler , Cheng Zhang , Manfred Opper , Stephan Mandt

In testing the independence of two Gaussian populations, one computes the distribution of the sample canonical correlation coefficients, given that the actual correlation is zero. The "Laplace transform" of this distribution is not only an…

Combinatorics · Mathematics 2007-05-23 M. Adler , P. van Moerbeke

We consider the nodal length $L(\lambda)$ of the restriction to a ball of radius $r_\lambda$ of a {\it Gaussian pullback monochromatic random wave} of parameter $\lambda>0$ associated with a Riemann surface $(\mathcal M,g)$ without…

Probability · Mathematics 2020-05-15 Gauthier Dierickx , Ivan Nourdin , Giovanni Peccati , Maurizia Rossi

A classical recursive construction for mutually orthogonal latin squares (MOLS) is shown to hold more generally for a class of permutation codes of length $n$ and minimum distance $n-1$. When such codes of length $p+1$ are included as…

Combinatorics · Mathematics 2019-08-02 Sergey Bereg , Peter Dukes

Let $p$ and $q$ be probability vectors with the same entropy $h$. Denote by $B(p)$ the Bernoulli shift indexed by $\Z$ with marginal distribution $p$. Suppose that $\phi$ is a measure preserving homomorphism from $B(p)$ to $B(q)$. We prove…

Probability · Mathematics 2007-07-13 Nate Harvey , Yuval Peres

An "entropy increasing to the maximum" result analogous to the entropic central limit theorem (Barron 1986; Artstein et al. 2004) is obtained in the discrete setting. This involves the thinning operation and a Poisson limit. Monotonic…

Information Theory · Computer Science 2009-11-18 Yaming Yu

In the probability theory limit distributions (or probability measures) are often characterized by some convolution equations (factorization properties) rather than by Fourier transforms (the characteristic functionals). In fact, usually…

Probability · Mathematics 2013-07-24 Zbigniew J. Jurek

In recent papers it has been demonstrated that sampling a Gibbs distribution from an appropriate time-irreversible Langevin process is, from several points of view, advantageous when compared to sampling from a time-reversible one. Adding…

Probability · Mathematics 2015-02-20 Luc Rey-Bellet , Konstantinos Spiliopoulos
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