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We study dynamical systems arising as time-dependent compositions of Pomeau-Manneville-type intermittent maps. We establish central limit theorems for appropriately scaled and centered Birkhoff-like partial sums, with estimates on the rate…

Dynamical Systems · Mathematics 2020-01-14 Olli Hella , Juho Leppänen

We investigate Bayesian predictive inference for finite population quantities when there are unequal probabilities of selection. Only limited information about the sample design is available; i.e., only the first-order selection…

Methodology · Statistics 2018-04-10 Junheng Ma , Joe Sedransk , Balgobin Nandram , Lu Chen

We prove several limit theorems that relate coalescent processes to continuous-state branching processes. Some of these theorems are stated in terms of the so-called generalized Fleming-Viot processes, which describe the evolution of a…

Probability · Mathematics 2007-05-23 Jean Bertoin , Jean-François Le Gall

Probability modelling for DNA sequence evolution is well established and provides a rich framework for understanding genetic variation between samples of individuals from one or more populations. We show that both classical and more recent…

Populations and Evolution · Quantitative Biology 2018-06-07 Asger Hobolth , Arno Siri-Jégousse , Mogens Bladt

We propose a nonparametric Bayesian factor regression model that accounts for uncertainty in the number of factors, and the relationship between factors. To accomplish this, we propose a sparse variant of the Indian Buffet Process and…

Machine Learning · Computer Science 2009-08-06 Piyush Rai , Hal Daumé

Coalescence processes have received a lot of attention in the context of conditional branching processes with fixed population size and non-overlapping generations. Here we focus on similar problems in the context of the standard…

Probability · Mathematics 2017-09-25 Nicolas Grosjean , Thierry Huillet

The following distributed coalescence protocol was introduced by Dahlia Malkhi in 2006 motivated by applications in social networking. Initially there are n agents wishing to coalesce into one cluster via a decentralized stochastic process,…

Probability · Mathematics 2015-03-17 Po-Shen Loh , Eyal Lubetzky

We consider joint probability distributions for the class of coupled Langevin equations introduced by Fogedby [H.C. Fogedby, Phys. Rev. E 50, 1657 (1994)]. We generalize well-known results for the single time probability distributions to…

Fluid Dynamics · Physics 2009-11-10 A. Baule , R. Friedrich

This paper studies the probabilistic function approximation problem over reproducing kernel Hilbert spaces. We show the existence and uniqueness of the optimizer under mild assumptions. Furthermore, we generalize the celebrated representer…

Functional Analysis · Mathematics 2025-07-16 Dongwei Chen , Kai-Hsiang Wang

Complex continuous or mixed joint distributions (e.g., P(Y | z_1, z_2, ..., z_N)) generally lack closed-form solutions, often necessitating approximations such as MCMC. This paper proposes Indeterminate Probability Theory (IPT), which makes…

Machine Learning · Computer Science 2025-06-24 Tao Yang , Chuang Liu , Xiaofeng Ma , Weijia Lu , Ning Wu , Bingyang Li , Zhifei Yang , Peng Liu , Lin Sun , Xiaodong Zhang , Can Zhang

We initiate a study of the following problem: Given a continuous domain $\Omega$ along with its convex hull $\mathcal{K}$, a point $A \in \mathcal{K}$ and a prior measure $\mu$ on $\Omega$, find the probability density over $\Omega$ whose…

Data Structures and Algorithms · Computer Science 2020-04-17 Jonathan Leake , Nisheeth K. Vishnoi

We construct a path distribution representing the kinetic part of the Feynman path integral at discrete times similar to that defined by Thomas [1], but on a Hilbert space of paths rather than a nuclear sequence space. We also consider…

Mathematical Physics · Physics 2015-10-30 Mathieu Beau , T. C. Dorlas

In this article, we derive statistical tools to analyze and distinguish the patterns of genetic variability produced by classical and recent population genetic models related to seed banks. In particular, we are concerned with models…

Populations and Evolution · Quantitative Biology 2020-01-10 Jochen Blath , Eugenio Buzzoni , Jere Koskela , Maite Wilke Berenguer

The Kingman coalescent is a fundamental process in population genetics modelling the ancestry of a sample of individuals backwards in time. In this paper, in a large-sample-size regime, we study asymptotic properties of the coalescent under…

Probability · Mathematics 2025-03-17 Martina Favero , Henrik Hult

The goal of this paper is to study the lookdown model with selection in the case of a population containing two types of individuals, with a reproduction model which is dual to the $\Lambda$-coalescent. In particular we formulate the…

Probability · Mathematics 2014-12-19 Boubacar Bah , Etienne Pardoux

We examine genetic statistics used in the study of structured populations. In a 1999 paper, Wakeley observed that the coalescent process associated with the finite island model can be decomposed into a scattering phase and a collecting…

Populations and Evolution · Quantitative Biology 2008-11-11 Sivan Leviyang

We study the multi-type Cannings population model. Each individual has a type belonging to a given at most countable type space $E$. The population is hence divided into $|E|$ subpopulations. The subpopulation sizes are assumed to be…

Probability · Mathematics 2025-04-16 Maximilian Flamm , Martin Möhle

We construct a new class of infinite-dimensional diffusions taking values in a generalized Kingman simplex. Our model describes the temporal evolution of the relative frequencies of infinitely-many types which are "labeled" by an arbitrary…

Probability · Mathematics 2026-02-25 Cristina Costantini , Matteo Ruggiero

Composition of low-dimensional distributions, whose foundations were laid in the papaer published in the Proceeding of UAI'97 (Jirousek 1997), appeared to be an alternative apparatus to describe multidimensional probabilistic models. In…

Artificial Intelligence · Computer Science 2013-01-18 Radim Jirousek

We construct a zig-zag process targeting a posterior distribution defined on a hybrid state space consisting of both discrete and continuous variables. The construction does not require any assumptions on the structure among discrete…

Computation · Statistics 2024-01-30 Jere Koskela
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