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The inverse problem method is tested for a class of mean field statistical mechanics models representing a mixture of particles of different species. The robustness of the inversion is investigated for different values of the physical…

Mathematical Physics · Physics 2015-06-12 M. Fedele , C. Vernia , P. Contucci

Two approaches are suggested to the definition of asymmetric generalized Weibull distribution. These approaches are based on the representation of the two-sided Weibull distributions as variance-mean normal mixtures or more general…

Probability · Mathematics 2015-06-23 Victor Korolev , Lily Kurmangazieva , Alexander Zeifman

In two recent articles we have examined a generalization of the binomial distribution associated with a sequence of positive numbers, involving asymmetric expressions of probabilities that break the symmetry {\it win-loss}. We present in…

Mathematical Physics · Physics 2015-06-17 H. Bergeron , E. M. F. Curado , J. P. Gazeau , Ligia M. C. S. Rodrigues

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

A new generalized matrix inverse is derived which is consistent with respect to arbitrary nonsingular diagonal transformations, e.g., it preserves units associated with variables under state space transformations, thus providing a general…

Numerical Analysis · Mathematics 2026-04-02 Jeffrey Uhlmann

We consider random permutation matrices following a one-parameter family of deformations of the uniform distribution, called Ewens' measures, and modifications of these matrices where the entries equal to one are replaced by i.i.d uniform…

Probability · Mathematics 2018-03-12 Valentin Bahier

Unfair predictions of machine learning (ML) models impede their broad acceptance in real-world settings. Tackling this arduous challenge first necessitates defining what it means for an ML model to be fair. This has been addressed by the ML…

Machine Learning · Computer Science 2024-08-30 Selim Kuzucu , Jiaee Cheong , Hatice Gunes , Sinan Kalkan

Arslan, Altoum, and Zaarour introduced an inversion statistic for generalized symmetric groups. In this work, we study the distribution of this statistic over colored permutations, including derangements and involutions. By establishing a…

Combinatorics · Mathematics 2025-05-06 Moussa Ahmia , José L. Ramírez , Diego Villamizar

This paper introduces a version of decoupling and randomization to establish concentration inequalities for double-indexed permutation statistics. The results yield, among other applications, a new combinatorial Hanson-Wright inequality and…

Statistics Theory · Mathematics 2026-03-23 Mingxuan Zou , Jingfan Xu , Peng Ding , Fang Han

We study fixed point biased involutions that avoid a pattern. For every pattern of length three we obtain limit theorems for the asymptotic distribution of the (appropriately centered and scaled) number of fixed points of a random fixed…

Probability · Mathematics 2026-01-01 Jungeun Park , Douglas Rizzolo

Testing the independence between random vectors is a fundamental problem in statistics. Distance correlation, a recently popular dependence measure, is universally consistent for testing independence against all distributions with finite…

Methodology · Statistics 2024-08-22 Yuwei Ke , Hok Kan Ling , Yanglei Song

In the statistical inference for long range dependent time series the shape of the limit distribution typically depends on unknown parameters. Therefore, we propose to use subsampling. We show the validity of subsampling for general…

Statistics Theory · Mathematics 2016-10-20 Annika Betken , Martin Wendler

In this article, we study a model of random permutations, which we call random standardized permutations, based on a sequence of i.i.d. random variables. This model generalizes others, such as the riffle-shuffle and the major-index-biased…

Probability · Mathematics 2026-03-26 Aurélien Guerder

Inverse problems, where in broad sense the task is to learn from the noisy response about some unknown function, usually represented as the argument of some known functional form, has received wide attention in the general scientific…

Methodology · Statistics 2017-07-24 Debashis Chatterjee , Sourabh Bhattacharya

Effective machine learning models can automatically learn useful information from a large quantity of data and provide decisions in a high accuracy. These models may, however, lead to unfair predictions in certain sense among the population…

Machine Learning · Computer Science 2020-06-19 Mingliang Chen , Min Wu

We survey recent results on some one- and two-dimensional patterns generated by random permutations of natural numbers. In the first part, we discuss properties of random walks, evolving on a one-dimensional regular lattice in discrete time…

Statistical Mechanics · Physics 2009-11-11 G. Oshanin , R. Voituriez , S. Nechaev , O. Vasilyev , F. Hivert

Permutation tests date back nearly a century to Fisher's randomized experiments, and remain an immensely popular statistical tool, used for testing hypotheses of independence between variables and other common inferential questions. Much of…

Methodology · Statistics 2022-12-05 Aaditya Ramdas , Rina Foygel Barber , Emmanuel J. Candes , Ryan J. Tibshirani

In this paper we study the cycle descent statistic on permutations. Several involutions on permutations and derangements are constructed. Moreover, we construct a bijection between negative cycle descent permutations and Callan perfect…

Combinatorics · Mathematics 2015-12-08 Jun Ma , Shimei Ma , Yeong-Nan Yeh , Zhu Xu

We prove a simple inequality for a sum of squares of norms of two vectors in an inner product space. Next, using this inequality we derive the so--called "reverse uncertainty relation" and analyze its properties.

Quantum Physics · Physics 2026-05-28 K. Urbanowski

We study the convergence of random function iterations for finding an invariant measure of the corresponding Markov operator. We call the problem of finding such an invariant measure the stochastic fixed point problem. This generalizes…

Functional Analysis · Mathematics 2022-03-24 Neal Hermer , D. Russell Luke , Anja Sturm
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