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Let A be a standard Borel space, and consider the space A^{\bbN^{(k)}} of A-valued arrays indexed by all size-k subsets of \bbN. This paper concerns random measures on such a space whose laws are invariant under the natural action of…

Probability · Mathematics 2015-07-09 Tim Austin

The problem of combining p-values is an old and fundamental one, and the classic assumption of independence is often violated or unverifiable in many applications. There are many well-known rules that can combine a set of arbitrarily…

Statistics Theory · Mathematics 2025-03-21 Matteo Gasparin , Ruodu Wang , Aaditya Ramdas

We extend classic characterisations of posterior distributions under Dirichlet process and gamma random measures priors to a dynamic framework. We consider the problem of learning, from indirect observations, two families of time-dependent…

Statistics Theory · Mathematics 2016-11-23 Omiros Papaspiliopoulos , Matteo Ruggiero , Dario Spanò

We study the optimal control of mean-field systems with heterogeneous and asymmetric interactions. This leads to considering a family of controlled Brownian diffusion processes with dynamics depending on the whole collection of marginal…

Probability · Mathematics 2024-07-29 Anna De Crescenzo , Marco Fuhrman , Idris Kharroubi , Huyên Pham

The study of almost surely discrete random probability measures is an active line of research in Bayesian nonparametrics. The idea of assuming interaction across the atoms of the random probability measure has recently spurred significant…

Statistics Theory · Mathematics 2025-04-25 Mario Beraha , Raffaele Argiento , Federico Camerlenghi , Alessandra Guglielmi

The Multiplicative Error Model (Engle (2002)) for nonnegative valued processes is specified as the product of a (conditionally autoregressive) scale factor and an innovation process with nonnegative support. A multivariate extension allows…

Statistical Finance · Quantitative Finance 2016-04-06 Fabrizio Cipollini , Robert F. Engle , Giampiero M. Gallo

We develop constructions for exchangeable sequences of point processes that are rendered conditionally-i.i.d. negative binomial processes by a (possibly unknown) random measure called the base measure. Negative binomial processes are useful…

Probability · Mathematics 2019-08-20 Creighton Heaukulani , Daniel M. Roy

Exchangeability is a central notion in statistics and probability theory. The assumption that an infinite sequence of data points is exchangeable is at the core of Bayesian statistics. However, finite exchangeability as a statistical…

Artificial Intelligence · Computer Science 2014-04-24 Mathias Niepert , Guy Van den Broeck

Infinite random sequences of letters can be viewed as stochastic chains or as strings produced by a source, in the sense of information theory. The relationship between Variable Length Markov Chains (VLMC) and probabilistic dynamical…

Probability · Mathematics 2010-07-20 Peggy Cénac , Brigitte Chauvin , Frédéric Paccaut , Nicolas Pouyanne

We introduce a new concept of dissipative measure-valued martingale solutions to the stochastic compressible Euler equations. These solutions are weak in the probabilistic sense i.e., the probability space and the driving Wiener process are…

Analysis of PDEs · Mathematics 2020-12-15 Martina Hofmanova , Ujjwal Koley , Utsab Sarkar

The competition between scrambling and projective measurements can lead to measurement-induced entanglement phase transitions (MIPT). In this work, we show that the universality class of the MIPT is drastically altered when the system is…

Quantum Physics · Physics 2024-10-04 Hyunsoo Ha , Akshat Pandey , Sarang Gopalakrishnan , David A. Huse

In inference problems involving a multi-dimensional parameter $\theta$, it is often natural to consider decision rules that have a risk which is invariant under some group $G$ of permutations of $\theta$. We show that this implies that the…

Methodology · Statistics 2014-07-01 Erik van Zwet

We study systems of particles on a line which have a maximum, are locally finite and evolve with independent increments. ``Quasi-stationary states'' are defined as probability measures, on the \sigma-algebra generated by the gap variables,…

Probability · Mathematics 2007-05-23 Anastasia Ruzmaikina , Michael Aizenman

We explore the class of exchangeable Bernoulli distributions building on their geometrical structure. Exchangeable Bernoulli probability mass functions are points in a convex polytope and we have found analytical expressions for their…

Statistics Theory · Mathematics 2021-01-20 Roberto Fontana , Patrizia Semeraro

Piecewise Deterministic Markov Processes (PDMPs) are studied in a general framework. First, different constructions are proven to be equivalent. Second, we introduce a coupling between two PDMPs following the same differential flow which…

Probability · Mathematics 2021-08-03 Alain Durmus , Arnaud Guillin , Pierre Monmarché

Permutation tests are a powerful and flexible approach to inference via resampling. As computational methods become more ubiquitous in the statistics curriculum, use of permutation tests has become more tractable. At the heart of the…

Methodology · Statistics 2025-06-09 Johanna Hardin , Lauren Quesada , Julie Ye , Nicholas J. Horton

Combinatorial Levy processes evolve on general state spaces of countable combinatorial structures. In this setting, the usual Levy process properties of stationary, independent increments are defined in an unconventional way in terms of the…

Probability · Mathematics 2016-12-20 Harry Crane

Failure times of a machinery cannot always be assumed independent and identically distributed, e.g. if after reparations the machinery is not restored to a same-as-new condition. Framed within the renewal processes approach, a…

Applications · Statistics 2019-05-14 Arrigo Coen , Luis Gutiérrez , Ramsés H. Mena

The transition law of every exchangeable Feller process on the space of countable graphs is determined by a $\sigma$-finite measure on the space of $\{0,1\}\times\{0,1\}$-valued arrays. In discrete-time, this characterization amounts to a…

Probability · Mathematics 2015-09-23 Harry Crane

Dirichlet process (DP) mixture models provide a flexible Bayesian framework for density estimation. Unfortunately, their flexibility comes at a cost: inference in DP mixture models is computationally expensive, even when conjugate…

Machine Learning · Computer Science 2009-07-13 Hal Daumé