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Multidimensional Continued Fraction Algorithms are generalizations of the Euclid algorithm and find iteratively the gcd of two or more numbers. They are defined as linear applications on some subcone of $\mathbb{R}^d$. We consider…

Dynamical Systems · Mathematics 2015-11-30 Sébastien Labbé

We exhibit a bijection between 132-avoiding permutations and Dyck paths. Using this bijection, it is shown that all the recently discovered results on generating functions for 132-avoiding permutations with a given number of occurrences of…

Combinatorics · Mathematics 2007-05-23 Christian Krattenthaler

Pattern avoidance classes of permutations that cannot be expressed as unions of proper subclasses can be described as the set of subpermutations of a single bijection. In the case that this bijection is a permutation of the natural numbers…

Combinatorics · Mathematics 2007-05-23 M. D. Atkinson , M. M. Murphy , N. Ruskuc

Dirichlet-multinomial (DMN) distribution is commonly used to model over-dispersion in count data. Precise and fast numerical computation of the DMN log-likelihood function is important for performing statistical inference using this…

Machine Learning · Statistics 2020-07-24 Djallel Bouneffouf

This note examines linear combinations of multi-indexed sequences and derives the multivariate generating function of such a linear combination in terms of the original sequence's m.g.f. Applications include finding distributions and…

Combinatorics · Mathematics 2012-09-18 Michael C. Burkhart

In this paper we introduce a new bijection from the set of Dyck paths to itself. This bijection has the property that it maps statistics that appeared recently in the study of pattern-avoiding permutations into classical statistics on Dyck…

Combinatorics · Mathematics 2007-05-23 Sergi Elizalde , Emeric Deutsch

In this paper we introduce and study a class of tableaux which we call permutation tableaux; these tableaux are naturally in bijection with permutations, and they are a distinguished subset of the Le-diagrams of Alex Postnikov. The…

Combinatorics · Mathematics 2007-05-23 Einar Steingrimsson , Lauren K. Williams

We exploit Krattenthaler's bijection between the set $S_n(3\textrm{-}1\textrm{-}2)$ of permutations in $S_n$ avoiding the classical pattern $3\textrm{-}1\textrm{-}2$ and Dyck $n$-paths to study the distribution of every consecutive pattern…

Combinatorics · Mathematics 2009-04-02 M. Barnabei , F. Bonetti , M. Silimbani

We consider the following basic, and very broad, statistical problem: Given a known high-dimensional distribution ${\cal D}$ over $\mathbb{R}^n$ and a collection of data points in $\mathbb{R}^n$, distinguish between the two possibilities…

Computational Complexity · Computer Science 2024-11-25 Anindya De , Huan Li , Shivam Nadimpalli , Rocco A. Servedio

In this paper a general theory of semi-classical matrix orthogonal polynomials is developed. We define the semi-classical linear functionals by means of a distributional equation $D(u A) = u B,$ where $A$ and $B$ are matrix polynomials.…

Classical Analysis and ODEs · Mathematics 2007-05-23 M. J. Cantero , L. Moral , L. Velazquez

We study the connections existing between max-infinitely divisible distributions and Poisson processes from the point of view of functional analysis. More precisely, we derive functional identities for the former by using well-known results…

Functional Analysis · Mathematics 2025-09-03 Bruno Costacèque-Cecchi , Laurent Decreusefond

Permutations that avoid given patterns are among the most classical objects in combinatorics and have strong connections to many fields of mathematics, computer science and biology. In this paper we study the scaling limits of a random…

Probability · Mathematics 2015-06-16 Christopher Hoffman , Douglas Rizzolo , Erik Slivken

We introduce a family of quasisymmetric functions called {\em Eulerian quasisymmetric functions}, which have the property of specializing to enumerators for the joint distribution of the permutation statistics, major index and excedance…

Combinatorics · Mathematics 2008-05-19 John Shareshian , Michelle L. Wachs

Bayesian models provide a framework for probabilistic modelling of complex datasets. However, many of such models are computationally demanding especially in the presence of large datasets. On the other hand, in sensor network applications,…

Machine Learning · Computer Science 2015-07-06 Behnam Babagholami-Mohamadabadi , Sejong Yoon , Vladimir Pavlovic

We derive some new signed Mahonian polynomials over the complex reflection group $G(r,1,n)=C_r\wr\mathfrak{S}_n$, where the "sign" is taken to be any of the $2r$ $1$-dim characters and the "Mahonian" statistics are the $\mathsf{lmaj}$…

Combinatorics · Mathematics 2019-02-26 Huilan Chang , Sen-Peng Eu , Shishuo Fu , Zhicong Lin , Yuan-Hsun Lo

An inequality for the variance of an additive function defined on random decomposable structures, called assemblies, is established. The result generalizes estimates obtained earlier in the cases of permutations and mappings of a finite set…

Combinatorics · Mathematics 2016-05-16 Eugenijus Manstavicius , Vytautas Stepas

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

Multidimensional record patterns are random sets of lattice points defined by means of a recursive stochastic construction. The patterns thus generated owe their richness to the fact that the construction is not based on a total order,…

Statistical Mechanics · Physics 2020-06-11 P. L. Krapivsky , J. M. Luck

Let $u(x)$ be a subpolynomial function in a Hardy field. We establish necessary and sufficient conditions for the weighted uniform distribution of the sequences $(u(n))_{n\in\mathbb{N}}$ and $(u(p_n))_{n\in\mathbb{N}}$, where $p_n$ denotes…

Number Theory · Mathematics 2025-09-25 Vitaly Bergelson , Grigori Kolesnik , Younghwan Son

Diffusions are a successful technique to sample from high-dimensional distributions. The target distribution can be either explicitly given or learnt from a collection of samples. They implement a diffusion process whose endpoint is a…

Machine Learning · Computer Science 2025-09-03 Andrea Montanari