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We study a method of seed-based lossless filtration for approximate string matching and related bioinformatics applications. The method is based on a simultaneous use of several spaced seeds rather than a single seed as studied by Burkhardt…

Quantitative Methods · Quantitative Biology 2011-01-18 Gregory Kucherov , Laurent Noé , Mikhail A. Roytberg

Sorting algorithms have attracted a great deal of attention and study, as they have numerous applications to Mathematics, Computer Science and related fields. In this thesis, we first deal with the mathematical analysis of the Quicksort…

Data Structures and Algorithms · Computer Science 2015-10-05 Vasileios Iliopoulos

We introduce and study some mixed product Poisson structures on product manifolds associated to Poisson Lie groups and Lie bialgebras. For quasitriangular Lie bialgebras, our construction is equivalent to that of fusion products of…

Differential Geometry · Mathematics 2016-01-12 Jiang-Hua Lu , Victor Mouquin

The Goulden$\unicode{x2013}$Jackson cluster method, adapted to permutations by Elizalde and Noy, reduces the problem of counting permutations by occurrences of a prescribed consecutive pattern to that of counting clusters, which are special…

Combinatorics · Mathematics 2023-05-19 Sergi Elizalde , Justin M. Troyka , Yan Zhuang

A matching of the set $[2n]=\{ 1,2,\ldots ,2n\}$ is a partition of $[2n]$ into blocks with two elements, i.e. a graph on $[2n]$ such that every vertex has degree one. Given two matchings $\sigma$ and $\tau$ , we say that $\sigma$ is a…

Combinatorics · Mathematics 2020-09-03 Matteo Cervetti , Luca Ferrari

Set partitions avoiding $k$-crossing and $k$-nesting have been extensively studied from the aspects of both combinatorics and mathematical biology. By using the generating tree technique, the obstinate kernel method and Zeilberger's…

Combinatorics · Mathematics 2017-07-11 Sherry H. F. Yan

The proposal and study of dependent prior processes has been a major research focus in the recent Bayesian nonparametric literature. In this paper, we introduce a flexible class of dependent nonparametric priors, investigate their…

Statistics Theory · Mathematics 2014-07-03 Antonio Lijoi , Bernardo Nipoti , Igor Prünster

To every poset P, Stanley (1986) associated two polytopes, the order polytope and the chain polytope, whose geometric properties reflect the combinatorial qualities of P. This construction allows for deep insights into combinatorics by way…

Combinatorics · Mathematics 2017-05-08 Thomas Chappell , Tobias Friedl , Raman Sanyal

In this article we survey properties of mixed Poisson distributions and probabilistic aspects of the Stirling transform: given a non-negative random variable $X$ with moment sequence $(\mu_s)_{s\in\mathbb{N}}$ we determine a discrete random…

Combinatorics · Mathematics 2014-09-12 Markus Kuba , Alois Panholzer

A novel approach to unstructured quadrilateral mesh generation for planar domains is presented. Away from irregular vertices, the resulting meshes have the properties of nearly conformal grids. The technique is based on a theoretical…

Computational Physics · Physics 2008-02-19 Guy Bunin

A popular approach to semi-supervised learning proceeds by endowing the input data with a graph structure in order to extract geometric information and incorporate it into a Bayesian framework. We introduce new theory that gives appropriate…

Machine Learning · Statistics 2020-01-14 Nicolas Garcia Trillos , Zachary Kaplan , Thabo Samakhoana , Daniel Sanz-Alonso

We study fishnet Feynman diagrams defined by a certain triangulation of a planar n-gon, with massless scalars propagating along and across the cuts. Our solution theory uses the technique of Separation of Variables, in combination with the…

High Energy Physics - Theory · Physics 2023-07-25 Francesco Aprile , Enrico Olivucci

This article focuses on inference in logistic regression for high-dimensional binary outcomes. A popular approach induces dependence across the outcomes by including latent factors in the linear predictor. Bayesian approaches are useful for…

Methodology · Statistics 2025-04-23 Lorenzo Mauri , David B. Dunson

We present a bijective algorithm with which an arbitrary permutation decomposes canonically into elementary blocks which we call families, which are sets with a specified number of ascents and descents. We show that families, arranged in an…

Combinatorics · Mathematics 2013-04-05 Adrian Ocneanu

Recent advances on overfitting Bayesian mixture models provide a solid and straightforward approach for inferring the underlying number of clusters and model parameters in heterogeneous datasets. The applicability of such a framework in…

Methodology · Statistics 2018-03-29 Panagiotis Papastamoulis

Real count data time series often show the phenomenon of the underdispersion and overdispersion. In this paper, we develop two extensions of the first-order integer-valued autoregressive process with Poisson innovations, based on binomial…

Methodology · Statistics 2020-07-27 Marcelo Bourguignon , Josemar Rodrigues , Manoel Santos-Neto

When working with multimodal Bayesian posterior distributions, Markov chain Monte Carlo (MCMC) algorithms have difficulty moving between modes, and default variational or mode-based approximate inferences will understate posterior…

Methodology · Statistics 2021-11-19 Yuling Yao , Aki Vehtari , Andrew Gelman

In 2011, Duncan and Steingr\'imsson conjectured that modified ascent sequences avoiding any of the patterns 212, 1212, 2132, 2213, 2231 and 2321 are counted by the Bell numbers. Furthermore, the distribution of the number of ascents is the…

Combinatorics · Mathematics 2024-10-17 Giulio Cerbai

This paper is a step-by-step tutorial for fitting a mixture distribution to data. It merely assumes the reader has the background of calculus and linear algebra. Other required background is briefly reviewed before explaining the main…

Other Statistics · Statistics 2020-10-13 Benyamin Ghojogh , Aydin Ghojogh , Mark Crowley , Fakhri Karray

Statistical inference on the mean of a Poisson distribution is a fundamentally important problem with modern applications in, e.g., particle physics. The discreteness of the Poisson distribution makes this problem surprisingly challenging,…

Methodology · Statistics 2012-07-03 Ryan Martin , Duncan Ermini Leaf , Chuanhai Liu
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