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This paper studies systems of particles following independent random walks and subject to annihilation, binary branching, coalescence, and deaths. In the case without annihilation, such systems have been studied in our 2005 paper…

Probability · Mathematics 2012-10-09 Siva Athreya , Jan Swart

We introduce a novel kernel that models input-dependent couplings across multiple latent processes. The pairwise joint kernel measures covariance along inputs and across different latent signals in a mutually-dependent fashion. A latent…

Machine Learning · Statistics 2017-10-04 Sami Remes , Markus Heinonen , Samuel Kaski

In this paper, we study different discrete data clustering methods, which use the Model-Based Clustering (MBC) framework with the Multinomial distribution. Our study comprises several relevant issues, such as initialization, model…

Machine Learning · Computer Science 2015-09-08 Md. Abul Hasnat , Julien Velcin , Stéphane Bonnevay , Julien Jacques

Coupled cluster theory is a vital cornerstone of electronic structure theory and is being applied to ever-larger systems. Stochastic approaches to quantum chemistry have grown in importance and offer compelling advantages over traditional…

In systems biomedicine, an experimenter encounters different potential sources of variation in data such as individual samples, multiple experimental conditions, and multi-variable network-level responses. In multiparametric cytometry,…

An electrodynamical coupled cluster (CC) methodology starting from a covariant formalism and an equal time approximation, and finally based on the Dirac-Fock picture of the electron and positron fields and Coulomb gauge, is given here. The…

Atomic Physics · Physics 2019-04-30 Sambhu N. Datta

A number of coupling strategies are presented for stochastically modeled biochemical processes with time-dependent parameters. In particular, the stacked coupling is introduced and is shown via a number of examples to provide an…

Numerical Analysis · Mathematics 2018-04-04 David F. Anderson , Chaojie Yuan

Nowadays, multiscale modelling is recognized as the most suitable way to study biological processes. Indeed, almost every phenomenon in nature exhibits a multiscale behaviour, i.e., it is the outcome of interactions that occur at different…

Formal Languages and Automata Theory · Computer Science 2011-08-18 Federico Buti , Massimo Callisto De Donato , Flavio Corradini , Emanuela Merelli , Luca Tesei

We analyse sequential Markov coalescent algorithms for populations with demographic structure: for a bottleneck model, a population-divergence model, and for a two-island model with migration. The sequential Markov coalescent method is an…

Populations and Evolution · Quantitative Biology 2025-10-01 A. Eriksson , B. Mahjani , B. Mehlig

Motivated by genetic association studies of pleiotropy, we propose here a Bayesian latent variable approach to jointly study multiple outcomes or phenotypes. The proposed method models both continuous and binary phenotypes, and it accounts…

Applications · Statistics 2012-11-08 Lizhen Xu , Radu V. Craiu , Lei Sun

We study the number of collisions $X_n$ of an exchangeable coalescent with multiple collisions ($\Lambda$-coalescent) which starts with $n$ particles and is driven by rates determined by a finite characteristic measure $\nu({\rm…

Probability · Mathematics 2008-07-18 Alexander Gnedin , Alex Iksanov , Martin Möhle

In the context of Markov processes, we show a new scheme to derive dual processes and a duality function based on a boson representation. This scheme is applicable to a case in which a generator is expressed by boson creation and…

Statistical Mechanics · Physics 2015-05-14 Jun Ohkubo

Compartmentalization of biochemical processes underlies all biological systems, from the organelle to the tissue scale. Theoretical models to study the interplay between noisy reaction dynamics and compartmentalization are sparse, and…

Quantitative Methods · Quantitative Biology 2022-06-08 Lorenzo Duso , Christoph Zechner

Duality relations between continuous-state and discrete-state stochastic processes with continuous-time have already been studied and used in various research fields. We propose extended duality relations, which enable us to derive…

Statistical Mechanics · Physics 2013-09-04 Jun Ohkubo

Homotopy approaches to Bayesian inference have found widespread use especially if the Kullback-Leibler divergence between the prior and the posterior distribution is large. Here we extend one of these homotopy approach to include an…

Numerical Analysis · Mathematics 2022-11-04 Sebastian Reich

We propose a discrete-time, finite-state stationary process that can possess long-range dependence. Among the interesting features of this process is that each state can have different long-term dependency, i.e., the indicator sequence can…

Probability · Mathematics 2022-09-19 Jeonghwa Lee

Obtaining a closed-form sampling distribution for the coalescent with recombination is a challenging problem. In the case of two loci, a new framework based on asymptotic series has recently been developed to derive closed-form results when…

Probability · Mathematics 2012-07-25 Anand Bhaskar , Yun S. Song

This article presents a concrete mathematical framework for the generation of entangled quantum states from classical stochastic processes. We demonstrate that any density operator $\rho_{AB}$ of a composite system can be derived from the…

Quantum Physics · Physics 2026-01-27 Andrei Khrennikov

This paper introduces the novel class of modulated cyclostationary processes, a class of non-stationary processes exhibiting frequency coupling, and proposes a method of their estimation from repeated trials. Cyclostationary processes also…

Methodology · Statistics 2012-10-25 Sofia C. Olhede , Hernando Ombao