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For a sample of Exponentially distributed durations we aim at point estimation and a confidence interval for its parameter. A duration is only observed if it has ended within a certain time interval, determined by a Uniform distribution.…

Methodology · Statistics 2021-10-19 Rafael Weißbach , Dominik Wied

Cut-elimination is the bedrock of proof theory. It is the algorithm that eliminates cuts from a sequent calculus proof that leads to cut-free calculi and applications. Cut-elimination applies to many logics irrespective of their semantics.…

Logic in Computer Science · Computer Science 2022-03-04 Agata Ciabattoni , Timo Lang , Revantha Ramanayake

Let $\eta_t$ be a Poisson point process of intensity $t\geq 1$ on some state space $\Y$ and $f$ be a non-negative symmetric function on $\Y^k$ for some $k\geq 1$. Applying $f$ to all $k$-tuples of distinct points of $\eta_t$ generates a…

Probability · Mathematics 2012-12-11 Matthias Schulte , Christoph Thaele

We define a sound and complete proof system for affine beta-eta-retractions in simple types built over many atoms, and we state simple necessary conditions for arbitrary beta-eta-retractions in simple and polymorphic types.

Logic in Computer Science · Computer Science 2007-05-23 Laurent Regnier , Pawel Urzyczyn

We extend results on time-rescaled occupation time fluctuation limits of the $(d,\alpha, \beta)$-branching particle system $(0<\alpha \leq 2, 0<\beta \leq 1)$ with Poisson initial condition. The earlier results in the homogeneous case…

Probability · Mathematics 2012-03-14 Tomasz Bojdecki , Luis G. Gorostiza , Anna Talarczyk

The Beta coalescents are stochastic processes modeling the genealogy of a population. They appear as the rescaled limits of the genealogical trees of numerous stochastic population models. In this article, we take interest in the number of…

Probability · Mathematics 2019-05-21 Yier Lin , Bastien Mallein

A semi-process is an analog of the semi-flow for non-autonomous differential equations or inclusions. We prove an abstract result on the existence of measurable semi-processes in the situations where there is no uniqueness. Also, we allow…

Dynamical Systems · Mathematics 2017-07-21 Jorge E. Cardona , Lev Kapitanski

Various specifiable combinatorial structures, with d extensive parameters, can be exactly sampled both by the recursive method, with linear arithmetic complexity if a heavy preprocessing is performed, or by the Boltzmann method, with…

Data Structures and Algorithms · Computer Science 2013-07-09 Frederique Bassino , Andrea Sportiello

Representation of coalescent process using pruning of trees has been used by Goldschmidt and Martin for the Bolthausen-Sznitman coalescent and by Abraham and Delmas for the $\beta(3/2,1/2)$-coalescent. By considering a pruning procedure on…

Probability · Mathematics 2015-01-08 Romain Abraham , Jean-Francois Delmas

The theory of sequences, supported by many SMT solvers, can model program data types including bounded arrays and lists. Sequences are parameterized by the element data type and provide operations such as accessing elements, concatenation,…

Programming Languages · Computer Science 2025-09-09 Denghang Hu , Taolue Chen , Philipp Rümmer , Fu Song , Zhilin Wu

We introduce an algorithm for detection of bugs in sequential circuits. This algorithm is incomplete i.e. its failure to find a bug breaking a property P does not imply that P holds. The appeal of incomplete algorithms is that they scale…

Logic in Computer Science · Computer Science 2013-09-26 Eugene Goldberg , Mitesh Jain , Panagiotis Manolios

We prove a large deviation principle for the point process of large Poisson $k$-nearest neighbor balls in hyperbolic space. More precisely, we consider a stationary Poisson point process of unit intensity in a growing sampling window in…

Probability · Mathematics 2023-04-19 Christian Hirsch , Moritz Otto , Takashi Owada , Christoph Thäle

Let $X$ be the branching particle diffusion corresponding to the operator $Lu+\beta (u^{2}-u)$ on $D\subseteq \mathbb{R}^{d}$ (where $\beta \geq 0$ and $\beta\not\equiv 0$). Let $\lambda_{c}$ denote the generalized principal eigenvalue for…

Probability · Mathematics 2007-09-04 Janos Englander , Simon C. Harris , Andreas E. Kyprianou

Consider a stationary renewal point process on the real line and divide each of the segments it defines in a proportion given by \iid realisations of a fixed distribution $G$ supported by [0,1]. We ask ourselves for which interpoint…

Probability · Mathematics 2014-08-12 Anton Muratov , Sergei Zuyev

$\beta$-decay, a process that changes a neutron into a proton (and vice versa), is the dominant decay mode of atomic nuclei. This decay offers a unique window to physics beyond the standard model, and is at the heart of microphysical…

We consider a one dimensional affine switched system obtained from a formal limit of a two dimensional linear system. We show this is equivalent to minimising the average digit in beta representations with unrestricted digits. We give a…

Optimization and Control · Mathematics 2025-09-11 Carl P. Dettmann

The paper establishes a functional version of the Hoeffding combinatorial central limit theorem. First, a pre-limiting Gaussian process approximation is defined, and is shown to be at a distance of the order of the Lyapounov ratio from the…

Probability · Mathematics 2009-07-03 A. D. Barbour , Svante Janson

This paper deals with Poisson processes on an arbitrary measurable space. Using a direct approach, we derive formulae for moments and cumulants of a vector of multiple Wiener-It\^o integrals with respect to the compensated Poisson process.…

Probability · Mathematics 2014-07-08 Guenter Last , Mathew D. Penrose , Matthias Schulte , Christoph Thaele

A new shrinkage-based construction is developed for a compressible vector $\boldsymbol{x}\in\mathbb{R}^n$, for cases in which the components of $\xv$ are naturally associated with a tree structure. Important examples are when $\xv$…

Machine Learning · Statistics 2014-01-14 Xin Yuan , Vinayak Rao , Shaobo Han , Lawrence Carin

One of the main challenges of Topological Data Analysis (TDA) is to extract features from persistent diagrams directly usable by machine learning algorithms. Indeed, persistence diagrams are intrinsically (multi-)sets of points in…

Machine Learning · Computer Science 2022-09-27 Raphael Reinauer , Matteo Caorsi , Nicolas Berkouk